[
 {
  "id": "dh-cognivue-clarity",
  "name": "Cognivue Clarity / Cognivue Thrive",
  "category": "cognitive-assessment",
  "developer": "Cognivue, Inc. (originally Cerebral Assessment Systems, Inc.)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2015-06-05",
  "intended_use": "Computerized cognitive assessment aid (FDA product code PKQ, 21 CFR 882.1470) granted via De Novo DEN130033; 10-minute self-administered visuomotor test for adults 55-95 at risk of age-related cognitive decline. Later Clarity/Thrive models are listed under the 510(k)-exempt code PTY (openFDA registration listing, created 2020-03-04).",
  "validated_population": "Adults 55-95 at outpatient clinics and assisted/independent-living facilities (cut-off study n=92; clinical validation n=401, of whom 358 completed two sessions) [Cahn-Hidalgo 2020, World J Psychiatry]. Bio-Hermes cohort n=887 with amyloid PET (388 cognitively normal, 282 MCI, 217 probable AD) [2024, Sci Rep].",
  "published_accuracy": "MEASURED. vs SLUMS reference (2020): weighted kappa 0.57 (95% CI 0.50-0.63); test-retest r=0.90; scores <=50 classified impaired, >=75 unimpaired. Bio-Hermes (2024, n=887): positive likelihood ratio 2.17, negative likelihood ratio 0.29, diagnostic odds ratio 7.48 for biomarker-confirmed MCI-AD/AD vs true controls; Cohen d 0.732 impaired vs normal. CARM amyloid measure (2025): OR 3.67 (95% CI 2.76-4.89) for amyloid-PET positivity (derived in the same cohort, not externally validated). Independent psychiatric-outpatient comparison (2021, n=58): only 43% agreement with MoCA; authors advised caution.",
  "evidence_strength": "Moderate: one manufacturer-run validation (2020) and one large biomarker-confirmed cross-sectional cohort (Bio-Hermes, 2024, industry-sponsored consortium). No sensitivity/specificity vs clinical diagnosis reported in abstracts; independent small study found poor MoCA agreement. Not validated for longitudinal progression.",
  "cost": "",
  "reimbursement_status": "Not verified from a loaded page (see CMS CPT 96146 item for the generic Medicare payment for automated computerized testing). Generic Medicare context (MEASURED, CMS Physician & Other Practitioners by Geography and Service, 2024 data, national): CPT 96146 (automated single-instrument electronic test administration) avg Medicare allowed $2.23 office / $2.14 facility, 8,782 office services to 4,470 beneficiaries by 207 providers; CPT 99483 (cognitive assessment & care plan) avg allowed $255.96 office / $180.23 facility, 130,107 office services to 117,441 beneficiaries; CPT 96136 (test administration first 30 min) avg allowed $39.87 office; CPT 96132 (neuropsych evaluation first hour) $124.09 office. No product-specific code; vendor reimbursement claims not verified.",
  "url": "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/denovo.cfm?ID=DEN130033",
  "notes": "Regulatory: openFDA device/510k record DEN130033 (decision 2015-06-05, product code PKQ, direct De Novo). Evidence: PMID 31956523 (doi 10.5498/wjp.v10.i1.1, 2020); PMID 39424626 (doi 10.1038/s41598-024-75304-5, 2024); PMID 40192926 (doi 10.1007/s40120-025-00741-x, 2025); PMID 34327120 (doi 10.5498/wjp.v11.i7.265, 2021 critique). Marketed claims beyond these (e.g., 'amyloid risk') rest on CARM derivation within Bio-Hermes only."
 },
 {
  "id": "dh-cantab-mobile",
  "name": "CANTAB Mobile / CANTAB Paired Associates Learning (PAL)",
  "category": "cognitive-assessment",
  "developer": "Cambridge Cognition Ltd",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2017-01-13",
  "intended_use": "510(k) K161328 (product code PKQ, Computerized Cognitive Assessment Aid), iPad-based PAL test for memory impairment in older adults, intended as aid to clinical assessment (openFDA 510k record).",
  "validated_population": "PAL has a 30-year literature in healthy volunteers, MCI and AD (review 2016). Recent diagnostic-accuracy study: 65 participants with MoCA-defined MCI (15/65) [2026, Acta Psychologica].",
  "published_accuracy": "MEASURED. PAL mean-errors-to-success AUC 0.80 (95% CI 0.66-0.95) for MoCA-defined MCI, cut-off 5.8: sensitivity 77%, specificity 74% (2026, n=65, small sample, MoCA as reference not clinical diagnosis).",
  "evidence_strength": "Moderate for construct validity (extensive PAL literature incl. fMRI hippocampal studies); weak for the specific CANTAB Mobile product as a screening tool (small diagnostic-accuracy samples; reference standard often another screener).",
  "cost": "",
  "reimbursement_status": "Generic Medicare context (MEASURED, CMS Physician & Other Practitioners by Geography and Service, 2024 data, national): CPT 96146 (automated single-instrument electronic test administration) avg Medicare allowed $2.23 office / $2.14 facility, 8,782 office services to 4,470 beneficiaries by 207 providers; CPT 99483 (cognitive assessment & care plan) avg allowed $255.96 office / $180.23 facility, 130,107 office services to 117,441 beneficiaries; CPT 96136 (test administration first 30 min) avg allowed $39.87 office; CPT 96132 (neuropsych evaluation first hour) $124.09 office. No product-specific code; vendor reimbursement claims not verified.",
  "url": "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K161328",
  "notes": "Regulatory: openFDA device/510k K161328, decision 2017-01-13, applicant Cambridge Cognition Ltd. Evidence: PMID 42567065 (doi 10.1016/j.actpsy.2026.107597, 2026); PMID 27646012 (doi 10.1007/7854_2015_5001, 2016 review); PMID 21477602 (2011 fMRI MCI). Widely used in trials (research-use platform) separate from the cleared clinical product."
 },
 {
  "id": "dh-linus-dctclock-dcr",
  "name": "Linus Health DCTclock / Digital Clock and Recall (DCR)",
  "category": "cognitive-assessment",
  "developer": "Linus Health, Inc. (DCTclock originally Digital Cognition Technologies)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "",
  "intended_use": "FDA-listed Class II 510(k)-exempt Computerized Cognitive Assessment Aid (product code PTY, 21 CFR 882.1470); openFDA registration listing 'Linus Health Platform'/'Linus Health Clinical Platform', listing created 2017-12-22, registration valid through 2026. Digitized clock-drawing analysed with machine learning; DCR adds a word-recall task. Note: 'FDA-listed/exempt' is not a reviewed clearance; no 510(k) number exists.",
  "validated_population": "DCTclock: 300 participants from Harvard Aging Brain Study / MGH PET lab (264 clinically normal, 143 with amyloid+tau PET; 36 MCI/early AD) [Rentz 2021, Neurology, Class II evidence]. DCR: Bio-Hermes-001 n=945 with external validation in Apheleia cohort n=238 [2026, Front Digit Health]. Framingham Heart Study dCDT: 87 low-age-risk adults with amyloid/tau PET [2025, Sci Rep].",
  "published_accuracy": "MEASURED. DCTclock AUC 0.86 for MCI/early AD vs clinically normal (n=300); among clinically normal, summary score discriminated amyloid+/- with Cohen d 0.76 vs 0.30 for PACC (2021). Framingham dCDT composite + demographics: mean AUC 0.86 for amyloid positivity (n=87, 2025, internal cross-validation). DCR-to-MMSE crosswalk model: RMSE 2.43 in held-out Bio-Hermes test set and 2.62 in external Apheleia cohort (2026) - this is one of the few digital tools with a reported external validation cohort.",
  "evidence_strength": "Moderate-to-strong for association with amyloid/tau PET and diagnostic discrimination in research cohorts; company-affiliated authorship on DCR papers; primary-care performance vs MoCA reported (JGIM 2026, correction noted) but abstract not loaded here.",
  "cost": "",
  "reimbursement_status": "Generic Medicare context (MEASURED, CMS Physician & Other Practitioners by Geography and Service, 2024 data, national): CPT 96146 (automated single-instrument electronic test administration) avg Medicare allowed $2.23 office / $2.14 facility, 8,782 office services to 4,470 beneficiaries by 207 providers; CPT 99483 (cognitive assessment & care plan) avg allowed $255.96 office / $180.23 facility, 130,107 office services to 117,441 beneficiaries; CPT 96136 (test administration first 30 min) avg allowed $39.87 office; CPT 96132 (neuropsych evaluation first hour) $124.09 office. No product-specific code; vendor reimbursement claims not verified.",
  "url": "https://doi.org/10.1212/WNL.0000000000011697",
  "notes": "REGULATORY NUANCE: this product is FDA-LISTED as a 510(k)-EXEMPT Class II device (product code PTY, 21 CFR 882.1470) - it has had NO FDA premarket review and has no K-number; it is coded 'FDA-cleared' only because the schema offers no 'FDA-listed/exempt' value. Vendor phrases such as 'FDA Class II' or 'FDA-registered' refer to this listing. Regulatory: openFDA device/registrationlisting, registration name 'Linus Health, Inc.', product code PTY, exempt. Evidence: PMID 33589537 (doi 10.1212/wnl.0000000000011697, 2021); PMID 42495050 (doi 10.3389/fdgth.2026.1799372, 2026); PMID 40169870 (doi 10.1038/s41598-025-95852-8, 2025); PMID 39533697 (2024, DCR vs FAQ functional impairment, no numbers in abstract)."
 },
 {
  "id": "dh-braincheck-assess",
  "name": "BrainCheck Assess",
  "category": "cognitive-assessment",
  "developer": "BrainCheck, Inc. (Austin, TX)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "",
  "intended_use": "FDA-listed Class II 510(k)-exempt Computerized Cognitive Assessment Aid (product code PTY); openFDA registration listing created 2017-11-08, valid through 2026. Tablet/phone battery (memory, attention, executive, processing speed) for cognitive impairment screening; remote self-administration studied.",
  "validated_population": "Groppell 2019: 583 volunteers >49 y from Houston community centres/living facilities (normative n=398; SLUMS n=84, MMSE n=51, MoCA n=35, physician-diagnosis n=18). Ye 2022: 99 participants with dementia, MCI or normal cognition. 2025 remote study: 46 adults 52-76.",
  "published_accuracy": "MEASURED. 2019 composite score vs screeners: sensitivity 81%, specificity 94% (reference mostly SLUMS/MMSE/MoCA, physician-diagnosed subgroup only n=18). 2022 (n=99): >=88% sensitivity and specificity for dementia vs normal; >=77% for MCI vs normal and vs dementia; three-group MCI true-positive rate >=64%. 2025 remote vs coordinator-administered ICC 0.59-0.83 (n=46).",
  "evidence_strength": "Weak-to-moderate: company-affiliated validation studies, small clinically diagnosed samples, no external multi-site validation; used as outcome measure in independent COVID cohorts (n=630) and an ED TBI feasibility study.",
  "cost": "",
  "reimbursement_status": "Generic Medicare context (MEASURED, CMS Physician & Other Practitioners by Geography and Service, 2024 data, national): CPT 96146 (automated single-instrument electronic test administration) avg Medicare allowed $2.23 office / $2.14 facility, 8,782 office services to 4,470 beneficiaries by 207 providers; CPT 99483 (cognitive assessment & care plan) avg allowed $255.96 office / $180.23 facility, 130,107 office services to 117,441 beneficiaries; CPT 96136 (test administration first 30 min) avg allowed $39.87 office; CPT 96132 (neuropsych evaluation first hour) $124.09 office. No product-specific code; vendor reimbursement claims not verified.",
  "url": "https://doi.org/10.2196/36825",
  "notes": "REGULATORY NUANCE: this product is FDA-LISTED as a 510(k)-EXEMPT Class II device (product code PTY, 21 CFR 882.1470) - it has had NO FDA premarket review and has no K-number; it is coded 'FDA-cleared' only because the schema offers no 'FDA-listed/exempt' value. Vendor phrases such as 'FDA Class II' or 'FDA-registered' refer to this listing. Regulatory: openFDA device/registrationlisting 'BRAINCHECK, INC.', proprietary name 'BrainCheck Assess', PTY exempt. Evidence: PMID 31518280 (doi 10.2196/12615, 2019, NCT03608722); PMID 35436212 (doi 10.2196/36825, 2022); PMID 40678715 (doi 10.3389/fdgth.2025.1571053, 2025); PMID 41943185 (2026 COVID cohort use)."
 },
 {
  "id": "dh-cogstate-cognigram",
  "name": "Cognigram (Cogstate Brief Battery)",
  "category": "cognitive-assessment",
  "developer": "Cogstate Ltd",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "",
  "intended_use": "FDA-listed Class II 510(k)-exempt Computerized Cognitive Assessment Aid (PTY); openFDA registration listing 'Cognigram', created 2017-11-06, valid through 2026. Card-based tasks (detection, identification, one-card learning, one-back) measuring psychomotor speed, attention, learning, working memory.",
  "validated_population": "2023 JAD: 4,871 cognitively unimpaired adults and 184 with MCI (CDR 0.5) or dementia (CDR >0.5) due to AD, CBB-naive. 2021 Alz Dement (Mayo Clinic Study of Aging, population-based): 2,866 cognitively unimpaired and 226 MCI, subset with amyloid/tau PET.",
  "published_accuracy": "MEASURED. 2023: Learning/Working-Memory composite AUC 0.90 for CDR 0.5 and 0.97 for CDR >0.5 vs unimpaired; individual learning/working-memory measures AUC ~0.79-0.88 (CDR 0.5) and ~0.89-0.96 (CDR >0.5). 2021 population-based: AUC 0.75 for all MCI vs unimpaired, 0.93 for CU A-T- vs MCI A+T+, 0.86 for MCI without vs with AD biomarkers; conventional cut-offs gave sensitivity only 38% (MCI) and 73% (prodromal AD) - authors: 'clinical utility ... lower than expected'.",
  "evidence_strength": "Moderate: large samples, but the population-based independent study shows much lower sensitivity than the enriched clinical sample; normative cut-offs flagged as unreliable.",
  "cost": "",
  "reimbursement_status": "Generic Medicare context (MEASURED, CMS Physician & Other Practitioners by Geography and Service, 2024 data, national): CPT 96146 (automated single-instrument electronic test administration) avg Medicare allowed $2.23 office / $2.14 facility, 8,782 office services to 4,470 beneficiaries by 207 providers; CPT 99483 (cognitive assessment & care plan) avg allowed $255.96 office / $180.23 facility, 130,107 office services to 117,441 beneficiaries; CPT 96136 (test administration first 30 min) avg allowed $39.87 office; CPT 96132 (neuropsych evaluation first hour) $124.09 office. No product-specific code; vendor reimbursement claims not verified.",
  "url": "https://doi.org/10.1002/alz.12219",
  "notes": "REGULATORY NUANCE: this product is FDA-LISTED as a 510(k)-EXEMPT Class II device (product code PTY, 21 CFR 882.1470) - it has had NO FDA premarket review and has no K-number; it is coded 'FDA-cleared' only because the schema offers no 'FDA-listed/exempt' value. Vendor phrases such as 'FDA Class II' or 'FDA-registered' refer to this listing. Regulatory: openFDA device/registrationlisting 'COGSTATE LTD', PTY exempt. Evidence: PMID 38007647 (doi 10.3233/jad-230352, 2023); PMID 33650308 (doi 10.1002/alz.12219, 2021). Cogstate also supplies research-use batteries for trials (separate from the listed clinical product)."
 },
 {
  "id": "dh-cns-vital-signs",
  "name": "CNS Vital Signs / Cognitrax",
  "category": "cognitive-assessment",
  "developer": "CNS Vital Signs LLC",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "",
  "intended_use": "FDA-listed Class II 510(k)-exempt Computerized Cognitive Assessment Aid (PTY); openFDA registration listing 'Cognitrax'/'CNS Vital Signs', created 2020-04-24, valid through 2026. Computerized versions of classic neuropsychological tests; marketed broadly (concussion, psychiatry, dementia).",
  "validated_population": "2025 Clin Neuropsychol: 73 cognitively healthy community-dwelling older adults (executive-function construct validity vs D-KEFS/WAIS-IV). Other recent studies loaded are in athletes (n=103) and TBI (n=49), not dementia.",
  "published_accuracy": "No dementia/MCI sensitivity, specificity or AUC located in Europe PMC search on 2026-09-22; construct validity of executive scores supported in healthy older adults (2025).",
  "evidence_strength": "Weak for dementia detection specifically (no diagnostic-accuracy study in dementia loaded); general psychometric literature exists.",
  "cost": "",
  "reimbursement_status": "Generic Medicare context (MEASURED, CMS Physician & Other Practitioners by Geography and Service, 2024 data, national): CPT 96146 (automated single-instrument electronic test administration) avg Medicare allowed $2.23 office / $2.14 facility, 8,782 office services to 4,470 beneficiaries by 207 providers; CPT 99483 (cognitive assessment & care plan) avg allowed $255.96 office / $180.23 facility, 130,107 office services to 117,441 beneficiaries; CPT 96136 (test administration first 30 min) avg allowed $39.87 office; CPT 96132 (neuropsych evaluation first hour) $124.09 office. No product-specific code; vendor reimbursement claims not verified.",
  "url": "https://doi.org/10.1080/13854046.2024.2354953",
  "notes": "REGULATORY NUANCE: this product is FDA-LISTED as a 510(k)-EXEMPT Class II device (product code PTY, 21 CFR 882.1470) - it has had NO FDA premarket review and has no K-number; it is coded 'FDA-cleared' only because the schema offers no 'FDA-listed/exempt' value. Vendor phrases such as 'FDA Class II' or 'FDA-registered' refer to this listing. Regulatory: openFDA device/registrationlisting 'CNS VITAL SIGNS', PTY exempt. Evidence: PMID 38763890 (2025). Honesty flag: dementia-screening use is marketed; evidence loaded here does not support a dementia accuracy claim."
 },
 {
  "id": "dh-creyos",
  "name": "Creyos (formerly Cambridge Brain Sciences)",
  "category": "cognitive-assessment",
  "developer": "Cambridge Brain Sciences Inc. o/a Creyos (Toronto)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "",
  "intended_use": "FDA-listed Class II 510(k)-exempt Computerized Cognitive Assessment Aid (PTY); openFDA registration listing 'Creyos', created 2024-02-20, valid through 2026. Web-based battery of 12 tasks; a two-task machine-learning MCI screener was described in 2026.",
  "validated_population": "2026 J Alzheimers Dis article describes a two-task screener for individuals on the AD continuum ('preliminary findings'); sample size and metrics not given in abstract. Feasibility as remote outcome in an acute stroke trial: only 242/791 (31%) completed Creyos (2025).",
  "published_accuracy": "Abstract states 'high sensitivity and specificity' for the two-task screener but gives no numbers; NOT recorded here as a measured value.",
  "evidence_strength": "Weak/preliminary for dementia screening; feasibility limitations in older, functionally impaired patients.",
  "cost": "",
  "reimbursement_status": "Generic Medicare context (MEASURED, CMS Physician & Other Practitioners by Geography and Service, 2024 data, national): CPT 96146 (automated single-instrument electronic test administration) avg Medicare allowed $2.23 office / $2.14 facility, 8,782 office services to 4,470 beneficiaries by 207 providers; CPT 99483 (cognitive assessment & care plan) avg allowed $255.96 office / $180.23 facility, 130,107 office services to 117,441 beneficiaries; CPT 96136 (test administration first 30 min) avg allowed $39.87 office; CPT 96132 (neuropsych evaluation first hour) $124.09 office. No product-specific code; vendor reimbursement claims not verified.",
  "url": "https://doi.org/10.1177/13872877261424289",
  "notes": "REGULATORY NUANCE: this product is FDA-LISTED as a 510(k)-EXEMPT Class II device (product code PTY, 21 CFR 882.1470) - it has had NO FDA premarket review and has no K-number; it is coded 'FDA-cleared' only because the schema offers no 'FDA-listed/exempt' value. Vendor phrases such as 'FDA Class II' or 'FDA-registered' refer to this listing. Regulatory: openFDA device/registrationlisting 'CAMBRIDGE BRAIN SCIENCES INC. (O/A CREYOS)', PTY exempt. Evidence: PMID 41848390 (2026); PMID 40071564 (2025 stroke-trial feasibility)."
 },
 {
  "id": "dh-neurotrack",
  "name": "Neurotrack Cognitive Assessment Battery",
  "category": "cognitive-assessment",
  "developer": "Neurotrack Technologies, Inc.",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "",
  "intended_use": "FDA-listed Class II 510(k)-exempt Computerized Cognitive Assessment Aid (PTY); openFDA registration listing created 2020-11-23, valid through 2026.",
  "validated_population": "",
  "published_accuracy": "None located: Europe PMC search for 'Neurotrack' in abstracts (SRC:MED) returned no results on 2026-09-22.",
  "evidence_strength": "No peer-reviewed diagnostic-accuracy evidence located; marketed product.",
  "cost": "",
  "reimbursement_status": "Generic Medicare context (MEASURED, CMS Physician & Other Practitioners by Geography and Service, 2024 data, national): CPT 96146 (automated single-instrument electronic test administration) avg Medicare allowed $2.23 office / $2.14 facility, 8,782 office services to 4,470 beneficiaries by 207 providers; CPT 99483 (cognitive assessment & care plan) avg allowed $255.96 office / $180.23 facility, 130,107 office services to 117,441 beneficiaries; CPT 96136 (test administration first 30 min) avg allowed $39.87 office; CPT 96132 (neuropsych evaluation first hour) $124.09 office. No product-specific code; vendor reimbursement claims not verified.",
  "url": "https://api.fda.gov/device/registrationlisting.json?search=registration.name:%22Neurotrack%22",
  "notes": "REGULATORY NUANCE: this product is FDA-LISTED as a 510(k)-EXEMPT Class II device (product code PTY, 21 CFR 882.1470) - it has had NO FDA premarket review and has no K-number; it is coded 'FDA-cleared' only because the schema offers no 'FDA-listed/exempt' value. Vendor phrases such as 'FDA Class II' or 'FDA-registered' refer to this listing. Included to document FDA listing status only. Honesty flag: any accuracy claims on vendor site are not evidence-backed by indexed literature found here."
 },
 {
  "id": "dh-cognica",
  "name": "CognICA / Integrated Cognitive Assessment (ICA)",
  "category": "cognitive-assessment",
  "developer": "Cognetivity Neurosciences (London/Vancouver)",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "5-minute, language-independent, image-categorisation test with an AI model to detect cognitive impairment; used in NHS ADePT primary-care referral study. FDA status: no record found in openFDA 510k or registration listing on 2026-09-22 (vendor claims not verified here); CE status not verified.",
  "validated_population": "2021 Front Psychiatry: 230 participants (95 healthy, 80 MCI, 55 mild AD). 2023 ADePT: 99 GP-referred memory-clinic patients aged 55-90, tested at home or clinic.",
  "published_accuracy": "MEASURED. AUC 0.81 for MCI and 0.88 for mild AD vs healthy (2021, n=230). ADePT (2023, n=99): sensitivity 93% for dementia, 83% for MCI, specificity 80%; test-retest agreement 87.5%; ICA correlation with education years 0.17 vs 0.34 (MoCA). Abstract states generalisability 'from one population to another' but no external cohort metrics given.",
  "evidence_strength": "Moderate: two company-affiliated studies with clinical-diagnosis reference; no independent external validation loaded.",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://doi.org/10.3389/fpsyt.2021.706695",
  "notes": "Evidence: PMID 34366938 (2021); PMID 37781102 (doi 10.3389/fnagi.2023.1243316, 2023). Regulatory status recorded as 'none' because it could not be verified from FDA databases; may be CE-marked per vendor but unverified."
 },
 {
  "id": "dh-altoida",
  "name": "Altoida (digital neuro-signature, AR-based)",
  "category": "cognitive-assessment",
  "developer": "Altoida, Inc.",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "10-minute tablet augmented-reality task battery producing a 'digital neuro signature' to detect MCI and predict cognitive decline. No openFDA 510(k), De Novo or registration-listing record found on 2026-09-22 (vendor-reported Breakthrough Device designation not verified from a loaded page).",
  "validated_population": "Altoida large cohort study (2022): Study A n=29 (MCI/AD, age 65+); Study B multicentre n=496 (213 MCI, 283 healthy controls); total 525 with FDG-PET, PiB PET, MRI. 2020 chapter describes a multi-site external validation study (AltoidaML) design only.",
  "published_accuracy": "MEASURED (association only). DNS-br total score significantly associated with FDG-PET resilience signature, PiB ratio and grey/white matter volume; predicts cognitive impairment for 80+ subgroup; interaction with time (less decline with higher score). No AUC/sensitivity/specificity given in abstract.",
  "evidence_strength": "Weak-to-moderate: company-affiliated cohort study; external validation study announced (2020) but results not located.",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://doi.org/10.3389/fpsyt.2022.899080",
  "notes": "Evidence: PMID 36061297 (2022); PMID 32468532 (doi 10.1007/978-3-030-32622-7_14, 2020). Honesty flag: marketed as a prognostic digital biomarker; published abstracts show associations, not validated prognostic accuracy."
 },
 {
  "id": "dh-brainsee",
  "name": "BrainSee",
  "category": "clinical-decision-support",
  "developer": "Darmiyan, Inc. (San Francisco)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2024-01-11",
  "intended_use": "De Novo DEN220066 (product code QWT, 21 CFR 882.1454 'Prognostic assessment software of mild cognitive impairment', Class II). Prescription software combining brain MRI, demographics and cognitive scores to output a 0-100 similarity score for likelihood that a patient aged 55-95 with amnestic MCI progresses to clinical AD-dementia (NINCDS-ADRDA) within 5 years. Adjunctive only; not for diagnosing aMCI. First FDA-authorized MCI prognostic software.",
  "validated_population": "Retrospective clinical validation: 198 aMCI patients with defined 5-year ground truth from 27 hospitals (118 converters, 80 non-converters); 209 additional eligible patients excluded for undefined ground truth (mostly incomplete 5-year follow-up). Demographics: 89.9% White, 3.5% Black, 3.5% Asian; 44.9% female; ages 55-94. FDA notes under-representation of non-White patients and requires a postmarket study with >=50% non-Caucasian and >=50% community-setting enrolment.",
  "published_accuracy": "MEASURED (FDA De Novo decision summary, cut-off 50): sensitivity 72.9% (95% CI 64.9-80.9), specificity 96.3% (92.1-100), PPV 97% (93-100), NPV 71% (62-79); TP 86, FN 32, FP 3, TN 77. No AUC reported. Lower CI bound for sensitivity fell below the pre-specified 70% goal; accepted because algorithm favours specificity. External validation: validation set was retrospective from 27 hospitals; the summary does not state whether these sites are independent of training data, and no peer-reviewed publication of the validation was located in Europe PMC.",
  "evidence_strength": "Moderate for regulatory performance (FDA-reviewed retrospective validation, n=198); weak for generalisability (predominantly White, research-quality MRI eligibility criteria, postmarket study mandated). No independent peer-reviewed external validation found.",
  "cost": "",
  "reimbursement_status": "No specific CPT/HCPCS code or Medicare coverage located.",
  "url": "https://www.accessdata.fda.gov/cdrh_docs/reviews/DEN220066.pdf",
  "notes": "Source: FDA De Novo classification order (accessdata cdrh_docs/pdf22/DEN220066.pdf) and De Novo decision summary (cdrh_docs/reviews/DEN220066.pdf), both loaded 2026-09-22; openFDA device/510k record DEN220066 decision_date 2024-01-11. Special controls require postmarket performance data in representative US population. Honesty flag: marketing may describe 'predicting Alzheimer's'; the cleared claim is adjunctive 5-year aMCI progression similarity scoring."
 },
 {
  "id": "dh-neuroquant",
  "name": "NeuroQuant (MRI volumetry) and NeuroQuant PET",
  "category": "AI-imaging",
  "developer": "Cortechs.ai (Cortechs Labs, Inc.), San Diego",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2006-08-10",
  "intended_use": "Automated MRI brain segmentation/volumetry with age- and sex-adjusted normative percentiles (hippocampal occupancy score etc.) to aid clinical assessment of neurodegeneration. 510(k)s: K061855 (2006-08-10, LLZ), K170981 (2017-09-07), K241098 (2024-08-22, QIH), OnQ Neuro K210831 (2021). NeuroQuant PET K261916 (2026-08-12, LLZ): regional/composite SUVR and Centiloid scoring for amyloid/FDG PET 'to support clinical interpretation of PET imaging performed for the assessment of cognitive impairment'.",
  "validated_population": "Independent memory-clinic studies: Oslo cohort n=366 (79 SCD, 86 MCI, 201 dementia; 217 AD vs 70 non-AD) [2025, Brain Behav]; Oslo n=86 (41 non-dementia, 45 dementia) [2024]; US academic memory clinic n=181 [2025, Cogn Behav Neurol]; ADNI n=192 MCI with 3-year follow-up [2017, AJNR]. NeuroQuant PET 510(k) testing: 14 of 62 subjects from NCT00785759 (PET-only input, expert-defined putamen/accumbens ROIs).",
  "published_accuracy": "MEASURED. Hippocampal percentile alone: AUC 0.85 for dementia vs SCD and 0.60 for AD vs non-AD (n=366, 2025); NQ hippocampal volume AUC 0.80 vs visual MTA 0.69 for dementia vs non-dementia (n=86, 2024). Memory-clinic study (n=181, 2025): sensitivity 0.31-0.77 and specificity 0.68-0.91 of hippocampal volumes/occupancy for objective memory impairment; correlation with CVLT-II r=0.20-0.44 - 'should be used cautiously'. MCI-to-AD 3-year conversion (ADNI n=192, 2017): hippocampal volume AUC 0.69; combining regions did not improve (0.60-0.63). NeuroQuant PET (FDA summary, 2026): 21-29% of subjects had paired SUVR differing >0.1 from expert ROIs (95% CI upper bounds 51-58%); FDA notes 'true performance limits may be less favorable than estimated'.",
  "evidence_strength": "Moderate for cross-sectional volumetric discrimination in independent clinical cohorts; weak-to-moderate as a prognostic tool (AUC ~0.69 for conversion). PET module has minimal published performance data (14 subjects in 510(k)).",
  "cost": "",
  "reimbursement_status": "MRI volumetry is generally billed as an add-on to the MRI read; no product-specific Medicare code verified here.",
  "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf26/K261916.pdf",
  "notes": "Regulatory: openFDA device/510k records (applicant Cortechs Labs, Inc.): K061855, K170981, K241098, K261916, K210831; FDA AI-enabled device list rows K170981, K241098, K210831. Evidence: PMID 41024716 (doi 10.1002/brb3.70948, 2025); PMID 38600026 (doi 10.1002/brb3.3397, 2024); PMID 40309995 (doi 10.1097/wnn.0000000000000390, 2025); PMID 28057634 (doi 10.3174/ajnr.a5061, 2017); PMID 37696909 (2023 brain-age comparison, NQ volumetrics >80% sens/spec dementia vs non-dementia, n=232)."
 },
 {
  "id": "dh-neuroreader",
  "name": "Neuroreader",
  "category": "AI-imaging",
  "developer": "Brainreader ApS (Horsens, Denmark)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2015-02-04",
  "intended_use": "510(k) K140828 (LLZ): automated MRI brain volumetry with normative comparison to aid assessment of atrophy. Also FDA-listed under LLZ/LNH (openFDA registration listing, 2015-04-07).",
  "validated_population": "ADNI n=192 MCI with 3-year follow-up (2017, AJNR, head-to-head with NeuroQuant); n=137 (40 TBI, 45 early-onset AD, 32 late-onset AD, 20 bvFTD) [2024, BMC Neurol].",
  "published_accuracy": "MEASURED. Hippocampal volume AUC 0.68 for MCI-to-AD conversion at 3 years (n=192, 2017; multivariable combinations 0.62-0.65, no improvement). 2024 diagnostic-group discrimination (TBI/EOAD/LOAD/bvFTD, n=137): AUCs 92.3-100%, sensitivity 82.2-100%, specificity 78.1-100% with leave-one-out cross-validation (internal validation only, small groups).",
  "evidence_strength": "Weak-to-moderate: prognostic accuracy modest; diagnostic-group results are internal cross-validation in a small single-centre sample.",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm?ID=K140828",
  "notes": "Regulatory: openFDA device/510k K140828 decision 2015-02-04 applicant Brainreader Aps. Evidence: PMID 28057634 (2017); PMID 39261753 (doi 10.1186/s12883-024-03844-4, 2024)."
 },
 {
  "id": "dh-icobrain-dm",
  "name": "icobrain dm",
  "category": "AI-imaging",
  "developer": "icometrix NV (Leuven, Belgium)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2016-08-09",
  "intended_use": "Automated MRI volumetry (hippocampi, lobes, ventricles, white-matter hyperintensities) with normative percentiles for differential diagnosis of dementia. 510(k)s K161148 (2016-08-09), K180326 (2018-03-08), K181939 (2018-11-06), K192130 (2019-12-13), all LLZ; also CE-marked (stated in 2021 JAD paper).",
  "validated_population": "Validation vs FreeSurfer and manual segmentation (2020, NeuroImage Clin). REMEMBER retrospective multi-centre clinical study (2021, JAD): 820 clinical T1 MRIs - 90 healthy controls, 93 SCD, 357 MCI, 280 AD dementia.",
  "published_accuracy": "MEASURED. Hippocampus Dice vs manual 0.86-0.88 (25th-75th percentile) vs FreeSurfer 0.80-0.83; temporal cortex volume AUC 0.99 AD vs controls in the 2020 development dataset. REMEMBER (n=820, real-world scans): best model HC vs AD dementia AUC 0.914, specificity 83.0%, sensitivity 86.3%; processing 15-30 min vs 9-32 h FreeSurfer; 0 vs 67 failures. No prognostic (MCI conversion) accuracy in loaded abstracts.",
  "evidence_strength": "Moderate: company-affiliated validation plus a multi-centre clinical-practice study; cross-sectional diagnosis only, not progression.",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://doi.org/10.3233/JAD-210450",
  "notes": "Regulatory: openFDA device/510k records applicant Icometrix NV. Evidence: PMID 32193172 (doi 10.1016/j.nicl.2020.102243, 2020); PMID 34334402 (doi 10.3233/jad-210450, 2021)."
 },
 {
  "id": "dh-icobrain-aria",
  "name": "icobrain aria",
  "category": "AI-imaging",
  "developer": "icometrix NV (Leuven, Belgium)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2024-11-07",
  "intended_use": "510(k) K240712 (product code QBS, 21 CFR 892.2090, computer-assisted detection). Deep-learning software assisting radiologists in detecting and quantifying amyloid-related imaging abnormalities (ARIA-E on 2D FLAIR, ARIA-H on T2*-GRE) on two-time-point MRI of AD patients on amyloid-beta-directed antibody therapy; outputs ARIA radiographic severity per FDA prescribing-information categories. Directly relevant to lecanemab/donanemab safety monitoring.",
  "validated_population": "Training: 475 FLAIR pairs (172 subjects, 51-85 y) and 326 T2*-GRE pairs (177 subjects) from aducanumab trials. Test set independent of training subjects: 199 MRI pairs from 199 subjects (mean age 70.4, 52.8% female, 78.9% White, 11.6% Asian, 0.5% Black), 33 scanners, >100 sites in 20 countries (~half US); extended set 1,015 FLAIR pairs/385 subjects and 449 GRE pairs/369 subjects. MRMC reader study: 16 US board-certified radiologists, 199 cases.",
  "published_accuracy": "MEASURED (FDA 510(k) summary). Standalone case-level: ARIA-E sensitivity 0.94 (95% CI 0.90-0.98), specificity 0.67 (0.56-0.77), AUC 0.84 (0.77-0.89); ARIA-H sensitivity 0.87, specificity 0.66, AUC 0.81; ARIA-H microhemorrhage AUC 0.80; superficial siderosis sensitivity 0.67, specificity 0.95, AUC 0.82. Finding-level TPR: new microhemorrhages 66.1% with 0.9 false positives/case; siderosis 62.5%. Reader study: assisted reading superior to unassisted for all ARIA types; ARIA-E sensitivity rose from 70.9% to 86.5%, siderosis 49.7% to 59.9%; specificity stayed >80% except 76.7% for mild ARIA-H microhemorrhages. External validation: test subjects independent of training, multi-site/multi-country, but drawn from the same sponsor trial ecosystem; no peer-reviewed independent validation located in Europe PMC.",
  "evidence_strength": "Moderate-to-strong for regulatory evidence (independent multi-site test set plus MRMC study); real-world post-market performance not yet published in indexed literature found here.",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf24/K240712.pdf",
  "notes": "Source: FDA 510(k) summary K240712 loaded 2026-09-22 (accessdata cdrh_docs/pdf24/K240712.pdf); FDA AI-enabled device list row 11/07/2024 K240712 icometrix NV Radiology QBS. Predicate OsteoDetect DEN180005."
 },
 {
  "id": "dh-qyscore",
  "name": "QyScore",
  "category": "AI-imaging",
  "developer": "Qynapse (Paris)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2019-12-13",
  "intended_use": "510(k) K192531 (LLZ): automatic volumetry of grey/white matter, hippocampus, amygdala and white-matter hyperintensities from 3D T1/FLAIR MRI with normative comparison; CE-marked (stated in 2022 Eur Radiol paper).",
  "validated_population": "Technical validation vs consensus of three expert neuroradiologists: 50 3D-T1 images (GM/WM/HP/AM) and 130 3D-T1+FLAIR (WMH) [2022, Eur Radiol].",
  "published_accuracy": "MEASURED (segmentation only): Dice/F1 lower CI bounds exceeded literature-derived reliability thresholds for GM, WM, hippocampus, amygdala and WMH; relative volume difference upper bounds below thresholds for WM, GM, HP, AM. No dementia diagnostic or prognostic accuracy loaded.",
  "evidence_strength": "Weak for clinical (diagnostic) claims; moderate for segmentation agreement with experts. Company-affiliated authors.",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://doi.org/10.1007/s00330-021-08385-9",
  "notes": "Regulatory: openFDA device/510k K192531 decision 2019-12-13 applicant Qynapse; FDA AI-enabled device list row 12/13/2019 K192531. Evidence: PMID 34973104 (2022)."
 },
 {
  "id": "dh-cneuro",
  "name": "cNeuro cMRI / cNeuro cPET (PredictAD lineage)",
  "category": "AI-imaging",
  "developer": "Combinostics Oy (Tampere, Finland)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2018-01-08",
  "intended_use": "cNeuro cMRI 510(k) K171328 (2018-01-08, LLZ): automated MRI volumetry/atrophy quantification with normative comparison. cNeuro cPET K231576 (2023-09-14, KPS): quantification of amyloid/FDG PET (SUVR). (cNeuro cDAT K233908, 2024, is a DaTscan/ioflupane tool for parkinsonism and is out of scope.) Lineage: EU PredictAD decision-support tool integrating MRI, CSF and neuropsychology.",
  "validated_population": "PredictAD tool study (2012, Dement Geriatr Cogn Disord): 140 ADNI MCI patients, 3 clinical raters classifying early AD with incremental data presentation.",
  "published_accuracy": "MEASURED (decision-support effect, not standalone accuracy): rater classification accuracy improved from 62.6% to 70.0% with the tool (p<0.05) and dropped to 63.2% when the same data were shown on paper (n=140, ADNI, 2012). No standalone AUC for the cleared cNeuro products located. FDA 510(k) summaries (loaded 2026-09-22): cNeuro cMRI K171328 tested on 1,399 subjects (healthy, AD, FTLD, vascular dementia, MS) - Dice 0.88 hippocampus, 0.91 thalamus, 0.88 whole cortex vs manual; test-retest ICC 0.96 averaged over 133 structures; FLAIR WMH correlation 0.97 with manual labels. cNeuro cPET K231576 tested on PET from 2,275 subjects (flutemetamol, florbetapir, florbetaben, FDG) incl. ADNI robustness, test-retest, and comparison with visual-read/histopathology standard of truth from florbetaben Phase III data; correlation with predicate R 0.98-0.99; Centiloids per Klunk et al. 2015 method. Sensitivity/specificity vs standard of truth were not in the loaded lines.",
  "evidence_strength": "Moderate for technical (segmentation/quantification) performance per FDA summaries with large test sets; weak for clinical diagnostic/prognostic accuracy (small ADNI reader study only).",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://doi.org/10.1159/000345554",
  "notes": "Regulatory: openFDA device/510k records applicant Combinostics OY: K171328, K231576, K233908; FDA AI-enabled device list row 01/08/2018 K171328. Evidence: PMID 23222123 (2012)."
 },
 {
  "id": "dh-neurophet-aqua-ad-plus",
  "name": "Neurophet AQUA AD Plus / Neurophet SCALE PET",
  "category": "AI-imaging",
  "developer": "Neurophet, Inc. (Seoul)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2026-01-29",
  "intended_use": "AQUA AD Plus 510(k) K252496 (2026-01-29, QIH): automatic labelling, visualization and volumetric quantification of brain structures and lesions (T1 segmentation, FLAIR hyperintensities, edema-like FLAIR hyperintensities, GRE/SWI hypointense lesions) plus SUVR/Centiloid quantification from MR+PET, with normative percentiles - i.e., an integrated volumetry + amyloid PET + ARIA-relevant lesion package. SCALE PET K221405 (2022-08-05) and K252563 (2026-05-15, QIH): amyloid/FDG PET SUVR and Centiloid. Neurophet AQUA K220437 (2023), K242215 (2024), K261273 (2026).",
  "validated_population": "FDA summary (AQUA AD Plus): training from ADNI, AIBL, PPMI and institutional sites (ages ~20-80+, White/Asian/Black; normal, MCI, AD, cerebrovascular, amyloid-related pathology). Validation on data separate from training: 60 T1 cases (segmentation), 136 FLAIR cases, 100 FLAIR edema cases from US/UK sites, 106 GRE/SWI cases from US sites, 30 paired MRI-PET for SUVR agreement, 176 paired MRI-amyloid PET from ADNI/AIBL for Centiloid classification.",
  "published_accuracy": "MEASURED (FDA 510(k) summary, technical accuracy only). T1 segmentation Dice 0.83 +/- 0.04 cortical, 0.87 +/- 0.03 subcortical; FLAIR lesion Dice 0.90 +/- 0.04; edema-like FLAIR Dice 0.91 +/- 0.09; GRE/SWI lesion median F1 0.860 (95% CI 0.824-0.902); SUVR ICC >=0.993 vs cleared reference (K221405) in 7 AD-relevant regions (n=30); Centiloid >=30 amyloid-positivity kappa >=0.70 vs expert visual reads (n=176). No dementia diagnostic or prognostic accuracy claimed or reported. No peer-reviewed clinical validation located in Europe PMC.",
  "evidence_strength": "Moderate for segmentation/quantification agreement (FDA-reviewed, held-out data); no clinical-outcome evidence.",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf25/K252496.pdf",
  "notes": "Source: FDA 510(k) summary K252496 loaded 2026-09-22; K252563 summary (Dice on 64 independent subjects; SUVR ICC >=0.937 FDG, >=0.990 amyloid vs K221405 in 74 paired datasets per tracer; Centiloid binary agreement in 176 ADNI/AIBL pairs, ICC 0.996); openFDA device/510k records applicant Neurophet., Inc.; FDA AI-enabled device list rows 01/29/2026 K252496 and 05/15/2026 K252563/K261273."
 },
 {
  "id": "dh-mim-centiloid",
  "name": "MIM - Centiloid Scaling (MIM Neuro)",
  "category": "AI-imaging",
  "developer": "MIM Software Inc. (Cleveland, OH)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2024-05-20",
  "intended_use": "510(k) K233620 (LLZ): extends MIM neuro PET/SPECT quantification (voxel-based z-scores vs normal database, regional SUVr) with conversion of SUVr to the standardized Centiloid scale for amyloid PET with florbetapir, florbetaben and flutemetamol. Not an AI classifier; quantification support for amyloid PET reads (relevant to anti-amyloid therapy eligibility).",
  "validated_population": "",
  "published_accuracy": "Not extracted: the 510(k) summary sections loaded describe substantial equivalence to MIM - Additional Tracers (K223800) and MIM 4.0 Neuro; no sensitivity/specificity figures were present in the grep of the summary.",
  "evidence_strength": "Regulatory equivalence only for this feature; the underlying Centiloid method is a published standard (Centiloid Project) but that source was not loaded here.",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf23/K233620.pdf",
  "notes": "Source: FDA 510(k) summary K233620 loaded 2026-09-22; openFDA device/510k applicant Mim Software, Inc. Honesty flag: included as a cleared quantification tool; no independent clinical accuracy data recorded."
 },
 {
  "id": "dh-ding2019-fdgpet-dl",
  "name": "Research model: deep learning on FDG-PET to predict final AD diagnosis (Ding et al., Radiology 2019)",
  "category": "AI-imaging",
  "developer": "UCSF Department of Radiology (academic)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "InceptionV3 convolutional neural network trained on 18F-FDG PET to predict final clinical diagnosis (AD / MCI / neither) years before diagnosis.",
  "validated_population": "Training/internal test: ADNI, 2,109 imaging studies from 1,002 patients (2005-2017), 90/10 split. External test: retrospective independent set of 40 studies from 40 patients (2006-2016) from the authors' institution.",
  "published_accuracy": "MEASURED. External independent test set (n=40): AUC 0.98 (95% CI 0.94-1.00) for final AD diagnosis; 82% specificity at 100% sensitivity, an average of 75.8 months before final diagnosis; outperformed radiologist readers (57% [4/7] sensitivity, 91% [30/33] specificity; P<.05). External validation: YES but very small (n=40, 7 AD cases, single institution).",
  "evidence_strength": "Moderate-to-weak: strong internal performance, tiny external test set; not prospectively validated; not a product.",
  "cost": "",
  "reimbursement_status": "Not applicable (research).",
  "url": "https://doi.org/10.1148/radiol.2018180958",
  "notes": "PMID 30398430, Radiology 2019 (published online 2018). Selected as a widely cited example of an externally tested imaging model; n and CI as stated in abstract loaded via Europe PMC 2026-09-22."
 },
 {
  "id": "dh-lu2018-multimodal-dl",
  "name": "Research model: multimodal/multiscale deep neural network on MRI + FDG-PET for MCI conversion (Lu et al., Sci Rep 2018)",
  "category": "AI-imaging",
  "developer": "McGill University / academic (Lu, Popuri, Ding, Balachandar, Beg; ADNI)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Deep neural network combining structural MRI and FDG-PET to discriminate AD and to predict which MCI individuals convert to AD.",
  "validated_population": "ADNI participants (exact n not stated in abstract). No external (non-ADNI) validation cohort mentioned.",
  "published_accuracy": "MEASURED (internal ADNI validation only): 82.4% accuracy identifying MCI converters 3 years before conversion (86.4% combined accuracy for conversion within 1-3 years); 94.23% sensitivity for probable AD; 86.3% specificity for non-demented controls. No AUC in abstract. External validation: NO.",
  "evidence_strength": "Weak-to-moderate: single-dataset (ADNI) internal validation; representative of the field's main weakness.",
  "cost": "",
  "reimbursement_status": "Not applicable (research).",
  "url": "https://doi.org/10.1038/s41598-018-22871-z",
  "notes": "PMID 29632364. Abstract loaded via Europe PMC 2026-09-22."
 },
 {
  "id": "dh-qiu2020-brain-interpretable-dl",
  "name": "Research model: interpretable deep learning on MRI + age/sex/MMSE for AD classification with three external cohorts (Qiu et al., Brain 2020)",
  "category": "AI-imaging",
  "developer": "Boston University (Qiu, Kolachalama et al.; academic)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Fully convolutional network producing voxel-level AD probability maps from MRI, fused with age, sex and MMSE in a multilayer perceptron for AD vs cognitively normal classification (cross-sectional diagnosis, not progression).",
  "validated_population": "Trained on ADNI (n=417, clinically diagnosed AD and cognitively normal); externally validated on AIBL (n=382), Framingham Heart Study (n=102) and NACC (n=582). Compared against 11 practicing neurologists; high-risk regions compared with post-mortem histopathology.",
  "published_accuracy": "MEASURED. Mean AUC 0.996 (ADNI), 0.974 (AIBL), 0.876 (FHS), 0.954 (NACC) for the multimodal model; exceeded the neurologist team's diagnostic performance. External validation: YES, three independent cohorts - one of the few AD imaging models with genuinely external testing; note the drop to 0.876 in the community-based FHS cohort.",
  "evidence_strength": "Strong for external validation of cross-sectional AD-vs-normal classification; does not address MCI progression, and AD-vs-normal is an easier task than clinically relevant differential diagnosis.",
  "cost": "",
  "reimbursement_status": "Not applicable (research). Follow-on multimodal framework (Qiu et al., Nat Commun 2022, PMID 35725739) extends to NC/MCI/AD/non-AD dementia with neuropathology comparison; abstract gives no AUC.",
  "url": "https://doi.org/10.1093/brain/awaa137",
  "notes": "PMID 32357201. Abstract loaded via Europe PMC 2026-09-22."
 },
 {
  "id": "dh-evidence-ansart2021-mci-ml-review",
  "name": "Evidence synthesis: machine learning for predicting MCI progression - systematic, quantitative and critical review (Ansart et al., Med Image Anal 2021)",
  "category": "AI-imaging",
  "developer": "Paris Brain Institute / Inria ARAMIS (academic)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Field-level appraisal of automatic MCI-to-AD progression prediction studies; included here because external validation is the field's known weak point and this review quantifies methodological problems.",
  "validated_population": "172 articles, 234 experiments extracted; multivariate mixed-effects regression of methodological choices on reported performance.",
  "published_accuracy": "MEASURED (meta-research): cognitive variables, FDG-PET and (potentially) EEG/MEG significantly improved predictive performance; T1 MRI did NOT show a significant effect. Absence of a test set, or use of the test set for feature selection/parameter tuning, in nearly one-fourth of papers; further issues casting doubt on clinical relevance in 15% of studies; short-term predictions likely not better than predicting stability. Authors state the good performance of cognitive assessments 'questions the wide use of imaging'.",
  "evidence_strength": "Strong (large systematic review with quantitative analysis). Key message for alzhub: published AUCs for progression models are frequently optimistic due to data leakage and lack of independent test sets.",
  "cost": "",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.1016/j.media.2020.101848",
  "notes": "PMID 33091740 (preprint doi 10.1101/2020.09.01.20185959). Abstract loaded via Europe PMC 2026-09-22."
 },
 {
  "id": "dh-evidence-grueso2021-mci-ml-review",
  "name": "Evidence synthesis: machine learning on neuroimaging for MCI-to-AD prediction - systematic review (Grueso & Viejo-Sobera, Alz Res Ther 2021)",
  "category": "AI-imaging",
  "developer": "Universitat Oberta de Catalunya (academic)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Systematic review (PRISMA) of ML applied to neuroimaging to predict MCI progression to AD dementia.",
  "validated_population": "452 studies screened, 116 included in qualitative analysis; datasets 'mainly extracted from ADNI with some exceptions'.",
  "published_accuracy": "MEASURED (meta-research): support vector machines mean accuracy 75.4%; convolutional neural networks mean accuracy 78.5%; MRI+PET combinations outperformed single modality; deep learning with multimodal/multidimensional data performed best. Predominance of a single dataset (ADNI) limits generalisability; external validation rarely performed.",
  "evidence_strength": "Strong as a field summary; note the modest mean accuracies (~75-79%) versus headline AUCs in individual papers.",
  "cost": "",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.1186/s13195-021-00900-w",
  "notes": "PMID 34583745. Abstract loaded via Europe PMC 2026-09-22."
 },
 {
  "id": "dh-evidence-2026-arr-dl-mci-conversion-review",
  "name": "Evidence synthesis: deep learning models for MCI-to-AD conversion, 2019-2026 systematic review (Ageing Research Reviews 2026)",
  "category": "AI-imaging",
  "developer": "Academic (authors not captured in loaded abstract)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "PRISMA systematic review of deep-learning models for AD stage classification and MCI-to-AD conversion prediction, articles 2019-01-01 to 2026-02-20 (PubMed, Scopus, IEEE Xplore, Web of Science).",
  "validated_population": "60 included studies: 47 cross-sectional, 13 longitudinal; 42 of 60 relied on ADNI; 24 multimodal; 21 CNN-based, 4 RNN, 4 transformer.",
  "published_accuracy": "MEASURED (meta-research): longitudinal designs 'heterogeneous but promising'; multimodal models often strong for MCI tasks; authors caution that cross-study comparisons are unreliable because of heterogeneity in datasets, tasks, validation strategies and methodological quality. 'Heavy reliance on the ADNI dataset (42 studies) represents a major limitation to generalizability.'",
  "evidence_strength": "Strong as the most recent field synthesis; confirms that external validation remains uncommon as of early 2026.",
  "cost": "",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.1016/j.arr.2026.103372",
  "notes": "PMID 42727648, pubYear 2026. Abstract loaded via Europe PMC 2026-09-22 (abstract truncated at results paragraph in the loaded record)."
 },
 {
  "id": "dh-winterlight-speech",
  "name": "Winterlight speech analysis platform",
  "category": "cognitive-assessment",
  "developer": "Winterlight Labs (Toronto; acquired by Cambridge Cognition)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Automated acoustic and linguistic feature extraction (>500 features) from picture-description or other speech tasks as a digital biomarker of cognitive impairment; used in trials and memory-clinic research. No FDA 510(k)/De Novo/listing record found in openFDA on 2026-09-22.",
  "validated_population": "109 memory-clinic patients with AD, FTD, vascular cognitive impairment etc. vs healthy adults (2024, Front Neurol); analytical validation in 122 ALS patients (2023); daily speech in 16 community volunteers for depression (2023).",
  "published_accuracy": "MEASURED (association only): linguistic features (shorter words, fewer prepositional phrases, fewer nouns/more pronouns) correlated with MMSE, DRS, WAB and BNT across diagnoses; patients had shorter speech with more pauses vs healthy adults. No diagnostic AUC in loaded dementia abstract.",
  "evidence_strength": "Weak-to-moderate for dementia: correlational evidence; no validated cut-offs or external diagnostic accuracy loaded.",
  "cost": "",
  "reimbursement_status": "Not applicable (research).",
  "url": "https://doi.org/10.3389/fneur.2024.1373341",
  "notes": "PMID 38590720 (2024); PMID 38144173 (2023 ALS analytical validation); PMID 37426590 (2023). Honesty flag: speech biomarkers are heavily marketed for 'early detection'; indexed evidence loaded here supports correlation with cognition, not screening accuracy."
 },
 {
  "id": "dh-moca-solo",
  "name": "MoCA Solo (self-administered digital MoCA)",
  "category": "cognitive-assessment",
  "developer": "MoCA Test Inc. (MoCA Cognition, Quebec)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "",
  "intended_use": "FDA-listed Class II 510(k)-exempt Computerized Cognitive Assessment Aid (PTY); openFDA registration listing 'MoCA Solo', created 2026-06-18. Self-administered digital version of the Montreal Cognitive Assessment.",
  "validated_population": "Not located for MoCA Solo specifically. Remote MoCA formats have validation: telephone T-MoCA in 153 older Korean adults (52 normal, 51 MCI, 50 dementia) showed AUCs not significantly different from in-person K-MoCA-30 (2026, J Korean Med Sci); telehealth video MoCA in rural US veterans: inter-rater reliability r=0.88-0.98 across in-person/telehealth conditions with no significant score differences (2019, J Telemed Telecare).",
  "published_accuracy": "No product-specific accuracy loaded (listing is recent). Remote-administration MoCA evidence above is MEASURED for telephone/video versions, not the self-administered product.",
  "evidence_strength": "Weak for the product; moderate for the underlying remote MoCA administration literature.",
  "cost": "",
  "reimbursement_status": "Generic Medicare context (MEASURED, CMS Physician & Other Practitioners by Geography and Service, 2024 data, national): CPT 96146 (automated single-instrument electronic test administration) avg Medicare allowed $2.23 office / $2.14 facility, 8,782 office services to 4,470 beneficiaries by 207 providers; CPT 99483 (cognitive assessment & care plan) avg allowed $255.96 office / $180.23 facility, 130,107 office services to 117,441 beneficiaries; CPT 96136 (test administration first 30 min) avg allowed $39.87 office; CPT 96132 (neuropsych evaluation first hour) $124.09 office. No product-specific code; vendor reimbursement claims not verified.",
  "url": "https://api.fda.gov/device/registrationlisting.json?search=proprietary_name:%22MoCA%22",
  "notes": "REGULATORY NUANCE: this product is FDA-LISTED as a 510(k)-EXEMPT Class II device (product code PTY, 21 CFR 882.1470) - it has had NO FDA premarket review and has no K-number; it is coded 'FDA-cleared' only because the schema offers no 'FDA-listed/exempt' value. Vendor phrases such as 'FDA Class II' or 'FDA-registered' refer to this listing. Regulatory: openFDA registrationlisting 'MOCA TEST INC.', PTY exempt, 2026-06-18. Remote MoCA evidence: PMID 42708484 (doi 10.3346/jkms.2026.41.e238); PMID 29320916 (doi 10.1177/1357633x17752030)."
 },
 {
  "id": "dh-care-ecosystem",
  "name": "Care Ecosystem (telephone/internet collaborative dementia care)",
  "category": "telehealth",
  "developer": "University of California San Francisco Memory and Aging Center (with University of Nebraska Medical Center)",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "Care-team-navigator-led collaborative dementia care delivered by telephone and internet from centralized hubs, with dementia specialist team (advanced practice nurse, social worker, pharmacist); 12-month programme for person-with-dementia/caregiver dyads regardless of health-system affiliation.",
  "validated_population": "Pragmatic single-blind RCT (NCT02213458): 780 dyads in California, Nebraska and Iowa enrolled 2015-2017 (512 intervention, 268 usual care); persons with dementia mean age 78.1, 56.3% female; English, Spanish or Cantonese speakers; Medicare/Medicaid-eligible; 571 completed 12-month survey.",
  "published_accuracy": "MEASURED outcomes at 12 months (intention-to-treat): quality of life (QoL-AD) improved B=0.53 (95% CI 0.25-1.30; P=.04); emergency department visits reduced B=-0.14 (95% CI -0.29 to -0.01; P=.04); caregiver depression (PHQ-9) B=-1.14 (95% CI -2.15 to -0.13; P=.03); caregiver burden (ZBI-12) B=-1.90 (95% CI -3.89 to -0.08; P=.046). End-of-life sub-study (2026): higher caregiver self-efficacy pre-death (beta 0.94, 95% CI 0.23-1.65, P=.01); satisfaction with EOL care not different (aOR 1.42, 95% CI 0.67-2.99).",
  "evidence_strength": "Strong: large pragmatic RCT published in JAMA Internal Medicine 2019; effect sizes modest; open-source implementation materials; adopted at 28 health systems and 8 community organizations including 22 GUIDE participants (2025).",
  "cost": "",
  "reimbursement_status": "Since 2024-07-01 the CMS GUIDE Model (8-year voluntary model) pays for care navigation, 24/7 support line, caregiver education and respite up to $2,500/year (CMS GUIDE page loaded 2026-09-22); 22 Care Ecosystem sites participate in GUIDE (JGS 2025). Exact GUIDE per-beneficiary payment rates were not captured from the loaded page.",
  "url": "https://doi.org/10.1001/jamainternmed.2019.4101",
  "notes": "PMID 31566651 (2019 RCT); PMID 39763029 (doi 10.1111/jgs.19363, 2025 dissemination); PMID 40827842 (2026 EOL outcomes); PMID 41292421 (2025 implementation qualitative). CMS GUIDE: https://www.cms.gov/priorities/innovation/innovation-models/guide."
 },
 {
  "id": "dh-ucla-adc-program",
  "name": "UCLA Alzheimer's and Dementia Care (ADC) Program",
  "category": "care-coordination",
  "developer": "UCLA Health",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "Nurse-practitioner/physician co-managed comprehensive dementia care: structured needs assessment, individualized care plans, community referrals, 24/7 clinician access. Predominantly in-person/telephone care management (not a telehealth product) - included as the comparator care-coordination model to Care Ecosystem.",
  "validated_population": "Quasi-experimental case-control: 1,083 Medicare FFS beneficiaries enrolled 2012-2015 (mean age 82.1) vs 2,166 propensity-matched non-participants.",
  "published_accuracy": "MEASURED (2019, JAMA Intern Med): long-term-care admission HR 0.60 (95% CI 0.59-0.61); no difference in hospitalizations, ED visits or 30-day readmissions; Medicare cost -$601 per patient-quarter (95% CI -$1,198 to -$5) excluding programme cost; net -$284 (95% CI -$881 to $312) after $317/quarter programme cost (cost-neutral). MODELLED elements: propensity matching, difference-in-differences.",
  "evidence_strength": "Moderate-to-strong observational evidence (not randomized); large claims-based outcomes.",
  "cost": "Programme cost estimated at $317 per patient per quarter (2012-2015 dollars, as reported).",
  "reimbursement_status": "Model of the type covered by CMS GUIDE from 2024-07-01.",
  "url": "https://doi.org/10.1001/jamainternmed.2018.5579",
  "notes": "PMID 30575846. Later ADC papers loaded: PMID 40485369 (2025 antipsychotic initiation), PMID 42414168 (2026 psychiatric hospitalization) - descriptive only."
 },
 {
  "id": "dh-va-home-video-telemedicine-dementia",
  "name": "VA home-based clinical video telehealth (Home-CVT) dementia clinic",
  "category": "telehealth",
  "developer": "US Department of Veterans Affairs, New England GRECC / VA Bedford Healthcare System",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "In-home video telemedicine visits for outpatients of a VA dementia clinic and their family caregivers (follow-up management, home safety occupational-therapy evaluation).",
  "validated_population": "230 families invited (2020 study); 96% responded; patients in telemedicine group slightly younger (mean 79 vs 84); 10 caregivers in home-safety OT evaluation study; 24 caregivers interviewed on barriers (2022).",
  "published_accuracy": "MEASURED (feasibility/satisfaction, not clinical outcomes): equivalent visit satisfaction between in-person and video visits; main reasons to enrol were convenience and less disruption; lack of a computer was the main reason to decline; participants demographically similar in race and education. No RCT outcomes.",
  "evidence_strength": "Weak (feasibility, satisfaction, qualitative); no effect on health outcomes measured.",
  "cost": "",
  "reimbursement_status": "VA-funded; outside Medicare fee schedule.",
  "url": "https://doi.org/10.1080/07317115.2019.1655510",
  "notes": "PMID 31431147 (2020); PMID 33520093 (2020 OT home safety); PMID 34096477 (2022 barriers/facilitators)."
 },
 {
  "id": "dh-va-pittsburgh-teledementia",
  "name": "VA Pittsburgh Teledementia clinic (clinical video telehealth to rural CBOCs)",
  "category": "telehealth",
  "developer": "VA Pittsburgh Healthcare System",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "Geriatric dementia consultation by clinical video telehealth to rural community-based outpatient clinics lacking geriatric expertise; medication optimization for veterans with dementia.",
  "validated_population": "199 CVT patient encounters, 1 Jan-31 Dec 2016.",
  "published_accuracy": "MEASURED (process outcomes, 2018): initial consults vs follow-ups had more medications added (0.731 vs 0.434 per encounter, p=0.0092), more total medication changes (1.769 vs 1.130, p=0.0078) and more 2015 Beers-criteria potentially inappropriate medications stopped (0.208 vs 0.072, p=0.0255). No patient-level clinical outcomes.",
  "evidence_strength": "Weak (single-site retrospective process evaluation).",
  "cost": "",
  "reimbursement_status": "VA-funded.",
  "url": "https://doi.org/10.3390/geriatrics3030044",
  "notes": "PMID 31011082 (Geriatrics 2018)."
 },
 {
  "id": "dh-tele-savvy",
  "name": "Tele-Savvy Caregiver Program",
  "category": "caregiver-app",
  "developer": "Emory University Nell Hodgson Woodruff School of Nursing (Hepburn, Griffiths et al.); online adaptation of the Savvy Caregiver Program",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "43-day online psychoeducation programme for family caregivers of community-dwelling persons living with dementia: 7 weekly synchronous videoconference sessions (groups of 6-8) plus 36 asynchronous video lessons; aims to raise caregiver mastery and reduce distress.",
  "validated_population": "Three-arm waitlist RCT (NCT03033875): 23 cohorts, N=261 caregivers randomized 2:2:1 to Tele-Savvy, attention control (Healthy Living), usual care; outcomes at 3, 6, 9, 12 months; trial slightly truncated due to COVID-19. Secondary analyses: 153 non-Hispanic Black and White caregivers; 137 for sleep outcomes.",
  "published_accuracy": "MEASURED (2022, Gerontologist): statistically and clinically significant benefits with moderate-to-large effect sizes for depression, perceived stress, reaction to care-recipient behaviours and caregiver mastery; NO significant effect on caregiver burden or anxiety. Race subgroup (2024): improvements in mastery and depression seen in White but not Black caregivers. Sleep (2023): insomnia severity improved over time (p=0.050), d=0.31; PSQI d=0.13.",
  "evidence_strength": "Strong (adequately powered RCT with attention control), with null results on burden/anxiety and differential benefit by race reported transparently.",
  "cost": "",
  "reimbursement_status": "Caregiver education is a GUIDE-covered service category from 2024-07-01; no direct product reimbursement.",
  "url": "https://doi.org/10.1093/geront/gnab029",
  "notes": "PMID 33640979 (2022 RCT); PMID 29399825 (2018 protocol); PMID 37067896 (2024 race subgroup); PMID 38111602 (2023 sleep); PMID 36990041 (2023 post-hospitalization qualitative)."
 },
 {
  "id": "dh-who-isupport",
  "name": "WHO iSupport for Dementia (online caregiver training and support)",
  "category": "caregiver-app",
  "developer": "World Health Organization; country adaptations (Australia - Flinders University; India; Netherlands; Portugal; Brazil; others)",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "Self-help, web-based psychoeducation and skills training for family carers of people with dementia (up to 23 lessons; also hardcopy manual); country versions add facilitators, peer support and service navigation.",
  "validated_population": "Virtual iSupport pragmatic RCT, Australia (ACTRN12622000199718; 2022-2024): 149 carers across four organizations, 12-month follow-up. Internal pilot RCT (n=84, Australia, 2022-2023); tailored vs usual Chinese iSupport pilot (n=78); India old-age-home carer training mixed-methods (n=35); India RCT protocol (target n=208, CTRI/2017/02/007876).",
  "published_accuracy": "MEASURED (Australia 2025, Alz Dement): intervention vs usual care at 12 months - carer mental-health-related QoL +12.0 points (p<0.001); self-efficacy +14.8 to +18.5 points (p<0.001); social support +0.25 (p<0.028); reactions to behaviour -0.25; 60% lower hospital admission rate for people with dementia (p=0.045). Pilot RCT (2026): no clear evidence of effect on QoL, social support or self-efficacy at 6 months; 70% retention. India (2022, pre-post n=35): knowledge median 12 to 17; attitude 30 to 33.5.",
  "evidence_strength": "Moderate: one positive pragmatic RCT (n=149, facilitator-enabled multicomponent version, not the bare self-help website), a null pilot, and pre-post studies; the unsupported self-help web version's efficacy remains less established. Multiple country RCT protocols registered; results for India RCT not located.",
  "cost": "Free to end users (WHO programme); implementation costs not captured.",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.1002/alz.70747",
  "notes": "PMID 41023309 (2025 RCT); PMID 42634407 (2026 pilot); PMID 40761086 (2025 Chinese pilot); PMID 36368147 (2022 India); PMID 29739423 (2018 India protocol); PMID 34783660 (2021 iSupport VA protocol); PMID 38873509 (2024 iSupport-Portugal early adopters n=365, 88.4% with significant burden)."
 },
 {
  "id": "dh-mastery-over-dementia",
  "name": "Mastery over Dementia (guided internet intervention for family caregivers)",
  "category": "caregiver-app",
  "developer": "VU University Amsterdam / Trimbos Institute (Blom, Pot et al.), Netherlands",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "Guided self-help internet course (8 lessons plus booster, psychologist feedback) to reduce depressive and anxiety symptoms in family caregivers of people with dementia.",
  "validated_population": "Pragmatic RCT (NTR-2051): 251 caregivers randomized (245 analysed; 149 intervention vs 96 minimal-intervention e-bulletins); predominantly female spouses/children; ages 26-87.",
  "published_accuracy": "MEASURED (2015, PLoS One, intention-to-treat): lower depressive symptoms (CES-D, p=.034, effect size 0.26) and anxiety (HADS-A, p=.007, effect size 0.48) post-intervention. Adherence: 55.7% did not complete all 8 lessons (2015 acceptability paper).",
  "evidence_strength": "Moderate-to-strong (RCT with small-to-moderate effects; high non-completion).",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://doi.org/10.1371/journal.pone.0116622",
  "notes": "PMID 25679228 (2015 RCT); PMID 25648589 (2015 acceptability); PMID 23305463 (2013 protocol)."
 },
 {
  "id": "dh-partner-in-balance",
  "name": "Partner in Balance (blended-care self-management programme)",
  "category": "caregiver-app",
  "developer": "Maastricht University / Alzheimer Centrum Limburg (Boots, de Vugt et al.), Netherlands",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "8-week blended programme for caregivers of people with early-stage dementia: face-to-face coaching plus tailored web modules; aims to increase self-efficacy and prevent later burden.",
  "validated_population": "Single-blind RCT (NTR4748): 81 caregivers of community-dwelling people with mild dementia (41 intervention, 40 waiting-list usual care). Cost-consequence analysis within waiting-list RCT n=78 (2026). Cluster-RCT with 24-month follow-up in progress (protocol 2023). Adapted for Huntington's disease (pilot n=18).",
  "published_accuracy": "MEASURED (2018, JMIR): significant gains in self-efficacy (care management P=.002, d=0.85; service use P=.001, d=0.93), mastery (P=.001, d=0.94) and quality of life (P=.032, d=0.58); NO effect on depression, anxiety or perceived stress. Cost-consequence (2026): higher 8-week costs EUR 2,027 vs EUR 805 (p=0.013), utility 0.82 vs 0.76 (p=0.073, n.s.); authors do not recommend reimbursement yet.",
  "evidence_strength": "Moderate (small RCT, proximal outcomes only; health-economic case unproven).",
  "cost": "EUR 2,027 mean 8-week intervention-plus-healthcare cost vs EUR 805 usual care (2026 Dutch analysis).",
  "reimbursement_status": "Not reimbursed; 2026 cost-consequence study advises awaiting long-term data.",
  "url": "https://doi.org/10.2196/10017",
  "notes": "PMID 30006327 (2018 RCT); PMID 29258980 (2017 process evaluation); PMID 41208238 (2026 cost-consequence); PMID 37349828 (2023 cluster-RCT protocol); PMID 39512474 (2024 HD pilot)."
 },
 {
  "id": "dh-tihm-iot-monitoring",
  "name": "TIHM (Technology Integrated Health Management) for dementia - NHS Test Bed IoT monitoring",
  "category": "remote-monitoring",
  "developer": "University of Surrey with Surrey and Borders Partnership NHS Foundation Trust (NHS England Test Bed programme)",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "Internet-of-Things home sensors plus vital-sign devices with machine-learning algorithms to detect and predict early signs of ill health, changes in routine, and agitation/irritability/aggression in people with dementia living at home; alerts monitored by a clinical team.",
  "validated_population": "Sensor data from homes of people with dementia in the TIHM deployment (number not stated in loaded abstracts).",
  "published_accuracy": "MEASURED (2018, PLoS One): hierarchical information-fusion approach recognised agitation and unusual activity patterns with accuracy of up to 80%. No clinical-outcome (hospitalization, crisis) results in the loaded abstracts.",
  "evidence_strength": "Weak-to-moderate: algorithm-level evaluation; outcome evaluation of the NHS deployment not located in indexed abstracts loaded here.",
  "cost": "",
  "reimbursement_status": "NHS-funded pilot; not applicable to Medicare. Generic Medicare RPM codes (MEASURED, CMS 2024 national physician/supplier data): CPT 99453 set-up avg allowed $20.22 office (211,468 services); 99454 device supply/30 days $47.80 office (2,155,063 services, 384,004 beneficiaries); 99457 first 20 min management $48.86 office (2,586,281 services); 99458 add-on $39.08 office. These are condition-agnostic; no dementia-specific RPM benefit exists.",
  "url": "https://doi.org/10.1371/journal.pone.0195605",
  "notes": "PMID 29723236 (2018); PMID 30290728 (2018 Br J Community Nurs description)."
 },
 {
  "id": "dh-orcatech-cart",
  "name": "ORCATECH / CART (Collaborative Aging Research using Technology) in-home monitoring platform",
  "category": "remote-monitoring",
  "developer": "Oregon Health & Science University ORCATECH (Kaye et al.); CART is an NIH/VA-funded multi-site initiative",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Unobtrusive continuous in-home assessment (passive infrared motion sensors, door contacts, computer-use monitoring, wearables, sleep mats) measuring walking speed, activity, time out of home, sleep, and social engagement to detect meaningful change and incident cognitive decline.",
  "validated_population": "ISAAC cohort (2011): 265 elderly persons (mean age 83.3, 73% women) monitored an average of 33 months. CART (2020): 232 homes, n=301 across four cohorts (African American, Latinx, low-income, rural veterans).",
  "published_accuracy": "MEASURED (descriptive feasibility): mean in-home walking speed 61.0 cm/s; participants left home twice daily for 208 min/day; computer use on 43% of days, 76 min/day (2011). CART: mean daily computer use 160-169 min; 96-155 room transitions/day; nightly sleep 6.3-7.4 h (2020). No diagnostic accuracy for cognitive decline in loaded abstracts (2011 paper states intent to test this). ISAAC walking-speed study (Dodge et al., Neurology 2012; 93 participants living alone: 54 intact, 31 non-amnestic MCI, 8 amnestic MCI; mean follow-up 2.6 y): latent-trajectory models found naMCI participants more likely in the slow weekly walking-speed trajectory (p=0.01 vs fast, p=0.04 vs moderate) and in the highest or lowest walking-speed-variability groups - association, not diagnostic accuracy.",
  "evidence_strength": "Moderate for feasibility and for association of in-home walking-speed trajectories with MCI (small n); no validated diagnostic thresholds.",
  "cost": "",
  "reimbursement_status": "Not applicable (research). Generic Medicare RPM codes (MEASURED, CMS 2024 national physician/supplier data): CPT 99453 set-up avg allowed $20.22 office (211,468 services); 99454 device supply/30 days $47.80 office (2,155,063 services, 384,004 beneficiaries); 99457 first 20 min management $48.86 office (2,586,281 services); 99458 add-on $39.08 office. These are condition-agnostic; no dementia-specific RPM benefit exists.",
  "url": "https://doi.org/10.1093/geronb/gbq095",
  "notes": "PMID 21743050 (2011); PMID 33442584 (doi 10.1159/000512208, 2020). PMID 22689734 (doi 10.1212/wnl.0b013e318259e1de, 2012)."
 },
 {
  "id": "dh-inhome-adl-sensors-urwyler2017",
  "name": "Research: in-home ADL-recognising sensors distinguishing dementia from healthy controls (Urwyler et al., Sci Rep 2017)",
  "category": "remote-monitoring",
  "developer": "University of Bern / academic",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Wireless unobtrusive home sensors recognising activities of daily living to quantify behavioural disorganisation in dementia.",
  "validated_population": "10 dementia patients and 10 healthy controls; ~9,600 person-hours of activity data.",
  "published_accuracy": "MEASURED: discriminating accuracy for dementia vs healthy increased with observation duration, reaching 0.95 at 20 days (n=20 total; internal analysis, no external validation).",
  "evidence_strength": "Weak (very small pilot).",
  "cost": "",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.1038/srep42084",
  "notes": "PMID 28176828. Included as representative of the small-n evidence base behind passive-monitoring marketing claims."
 },
 {
  "id": "dh-ukbiobank-axivity-steps-dementia",
  "name": "Wrist accelerometer (Axivity AX3) step count and incident dementia - UK Biobank (del Pozo Cruz et al., JAMA Neurol 2022)",
  "category": "wearable",
  "developer": "UK Biobank accelerometry sub-study (device: Axivity AX3 wrist-worn triaxial accelerometer); analysis by University of Sydney/University of Southern Denmark",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Population-level evidence linking device-measured daily steps and cadence to all-cause dementia risk; the basis for step-based prevention guidance.",
  "validated_population": "78,430 of 103,684 eligible UK adults aged 40-79 with valid wrist-accelerometer data (Feb 2013-Dec 2015); mean age 61.1; 96.7% White; median follow-up 6.9 years; 866 incident dementia cases (registry/hospital/primary-care/death linkage to Oct 2021).",
  "published_accuracy": "MEASURED (observational association, spline Cox models): optimal dose 9,826 steps/day HR 0.49 (95% CI 0.39-0.62); minimal dose 3,826 steps HR 0.75 (0.67-0.83); purposeful-cadence optimal dose 6,315 steps HR 0.43 (0.32-0.58); peak 30-min cadence 112 steps/min HR 0.38 (0.24-0.60). Not a diagnostic accuracy study; reverse causation possible.",
  "evidence_strength": "Strong observational cohort (large n, device-measured exposure, linked outcomes); causal inference limited.",
  "cost": "",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.1001/jamaneurol.2022.2672",
  "notes": "PMID 36066874. Abstract loaded via Europe PMC 2026-09-22."
 },
 {
  "id": "dh-axivity-gait-dementia-subtypes",
  "name": "Single accelerometer wearable (Axivity) gait analysis to differentiate dementia subtypes (Mc Ardle et al., Gait Posture 2020)",
  "category": "wearable",
  "developer": "Newcastle University Brain and Movement Research Group (academic)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Lower-back accelerometer-derived spatiotemporal gait characteristics (pace, variability, rhythm, asymmetry, postural control) as differential markers for AD vs dementia with Lewy bodies vs Parkinson's disease dementia.",
  "validated_population": "80 people with MCI or dementia due to AD, DLB or PD performing six 10-m walks.",
  "published_accuracy": "MEASURED: significant between-group differences in 7 of 14 gait characteristics (vs 2 for an instrumented walkway); ROC/AUC described as 'modest accuracy' for single characteristics (values not in abstract). Internal analysis only.",
  "evidence_strength": "Weak-to-moderate (small single-centre feasibility).",
  "cost": "",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.1016/j.gaitpost.2019.12.028",
  "notes": "PMID 31901765. Systematic review of wearable gait assessment in dementia found only 6 eligible studies (PMID 34886459, 2021)."
 },
 {
  "id": "dh-waist-imu-mci-2026",
  "name": "Research: waist-mounted IMU multi-domain gait analysis for MCI identification (IEEE TNSRE 2026)",
  "category": "wearable",
  "developer": "Academic (authors not captured)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Inertial measurement unit features across time, frequency, nonlinear and time-frequency domains during SPPB assessment, with SVM classifier and association-rule mining to screen for MCI.",
  "validated_population": "Older adults in a field study (n not in abstract).",
  "published_accuracy": "MEASURED (internal cross-validation): mean test AUC 0.897, accuracy 0.828 (SVM). External validation: NO.",
  "evidence_strength": "Weak (single study, internal validation, n unspecified in abstract).",
  "cost": "",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.1109/TNSRE.2026.3708678",
  "notes": "PMID 42378146. Included to show typical reported AUCs for wearable-gait MCI screening lack external validation."
 },
 {
  "id": "dh-apple-watch-cognitive-monitoring",
  "name": "Apple Watch consumer wearable in cognitive impairment research (myRhythmWatch; Amissa platform)",
  "category": "wearable",
  "developer": "Apple Inc. (device); research platforms by academic groups (myRhythmWatch) and Amissa Health",
  "regulatory_status": "none",
  "clearance_date": "",
  "intended_use": "Consumer smartwatch accelerometry/heart-rate/sleep streams repurposed for 24-hour sleep/wake rhythm and activity monitoring in older adults with and without MCI/dementia. Apple Watch itself has no FDA authorization for cognition (its ECG/AFib features are separate).",
  "validated_population": "myRhythmWatch feasibility (2025, JMIR): 40 adults (19 MCI, 21 no cognitive disorder), mean age 67.2, 1 week. Amissa case series (2025, J Gerontol A): 7 neurologist-diagnosed cognitively impaired participants, 6 months. Preference study (2026): 9 Black older adults/care partners rated Apple Watch SE highest on comfort/features.",
  "published_accuracy": "MEASURED (feasibility/association only): 100% provided >=3 valid days; later activity onset associated with worse delayed memory (beta=-0.28); more fragmented rhythms with worse processing speed (beta=0.40). Amissa: mean wear 11.48 h/day on 84.91% of days over 6 months; >700,000 observations. No diagnostic accuracy.",
  "evidence_strength": "Weak (feasibility). Honesty flag: consumer wearables are marketed for 'brain health'; loaded evidence shows only feasibility and cross-sectional correlations.",
  "cost": "",
  "reimbursement_status": "Consumer purchase; not reimbursed. Generic Medicare RPM codes (MEASURED, CMS 2024 national physician/supplier data): CPT 99453 set-up avg allowed $20.22 office (211,468 services); 99454 device supply/30 days $47.80 office (2,155,063 services, 384,004 beneficiaries); 99457 first 20 min management $48.86 office (2,586,281 services); 99458 add-on $39.08 office. These are condition-agnostic; no dementia-specific RPM benefit exists.",
  "url": "https://doi.org/10.2196/67294",
  "notes": "PMID 40194310 (2025); PMID 39478338 (doi 10.1093/gerona/glae250, 2025); PMID 41853222 (2026)."
 },
 {
  "id": "dh-evidence-telehealth-dementia-meta-analyses-2026",
  "name": "Evidence synthesis: telehealth/telemedicine interventions for people with dementia - 2026 systematic reviews and meta-analyses of RCTs",
  "category": "telehealth",
  "developer": "Academic (three independent review teams, 2026)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Field-level summary of RCT evidence for telehealth-delivered interventions (video, device, software; cognitive training, movement programmes, caregiver support) in older adults with dementia/MCI.",
  "validated_population": "Review A (Arch Psychiatr Nurs 2026): 12 RCTs, 822 people with dementia, 5 countries. Review B (J Telemed Telecare 2026): 12 RCTs, 21,500 participants (adults >=60 with dementia). Review C (Healthc Technol Lett 2026): 14 RCTs (search 11 Aug 2025).",
  "published_accuracy": "MEASURED (pooled). Review A: cognitive function SMD 1.00 (95% CI 0.56-1.43), executive function SMD -0.62 (-1.12 to -0.13), QoL SMD 0.72 (0.24-1.20). Review B: significant ADL improvement (Z=2.63, P<0.05, I2=1%) but NO effect on cognition, depression, caregiver burden or transfer rates; high heterogeneity (I2 81.6% cognition, 87% depression). Review C: 13 of 14 trials reported benefits; small samples noted. The conflicting pooled results between A and B (same year, overlapping question) show the evidence is heterogeneous and sensitive to inclusion criteria.",
  "evidence_strength": "Mixed: RCT-level evidence exists but small trials, heterogeneous interventions, and inconsistent pooled findings; 'telehealth improves cognition' should not be stated as settled.",
  "cost": "",
  "reimbursement_status": "Medicare telehealth flexibilities and the GUIDE Model (2024-07-01) are the US payment context; not captured in detail here.",
  "url": "https://doi.org/10.1177/1357633X261447401",
  "notes": "PMID 41956601 (doi 10.1016/j.apnu.2026.152101); PMID 42084481 (doi 10.1177/1357633x261447401); PMID 41685378 (doi 10.1049/htl2.70065); PMID 41716125 (2026 implementation barriers review, 25 papers, 14 countries)."
 },
 {
  "id": "dh-rush-map-actigraphy-activity-ad",
  "name": "Wrist actigraphy (Philips Actical) total daily physical activity and incident AD - Rush Memory and Aging Project (Buchman et al., Neurology 2012)",
  "category": "wearable",
  "developer": "Rush Alzheimer's Disease Center, Chicago (academic); device Actical, Philips Healthcare",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Objective actigraphic measure of total daily (exercise plus non-exercise) physical activity as a predictor of incident clinical AD and cognitive decline.",
  "validated_population": "716 older adults without dementia in the Rush Memory and Aging Project; up to 10 days of continuous actigraphy; annual clinical examination with 19 cognitive tests; ~4-year average follow-up; 71 developed clinical AD.",
  "published_accuracy": "MEASURED (observational): total daily physical activity associated with incident AD, HR 0.477 (95% CI 0.273-0.832), robust to adjustment for self-reported activities, motor function, depressive symptoms, chronic conditions and APOE; associated with rate of global cognitive decline (estimate 0.033, SE 0.012, p=0.007).",
  "evidence_strength": "Strong observational cohort evidence for actigraphy-measured activity as a risk marker; not a diagnostic device.",
  "cost": "",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.1212/WNL.0b013e3182535d35",
  "notes": "PMID 22517108 (PMCID PMC3335448). Abstract loaded via NCBI E-utilities 2026-09-22."
 },
 {
  "id": "dh-rush-map-actigraphy-sleep-fragmentation-ad",
  "name": "Actigraphy-derived sleep fragmentation and incident AD - Rush Memory and Aging Project (Lim et al., Sleep 2013)",
  "category": "wearable",
  "developer": "Rush Alzheimer's Disease Center / Sunnybrook, University of Toronto (academic)",
  "regulatory_status": "research-use-only",
  "clearance_date": "",
  "intended_use": "Actigraphic sleep fragmentation metric as a prospective risk marker for AD and cognitive decline.",
  "validated_population": "737 community-dwelling older adults without dementia; up to 10 consecutive days of actigraphy; follow-up up to 6 years (mean 3.3); 97 developed AD.",
  "published_accuracy": "MEASURED (observational): HR 1.22 (95% CI 1.03-1.44, P=0.02) per 1 SD increase in sleep fragmentation; 90th vs 10th percentile 1.5-fold AD risk; 0.01-unit increase in fragmentation associated with 22% faster annual cognitive decline (P=0.03). Independent of total rest time, medical conditions and sleep-affecting medications.",
  "evidence_strength": "Strong observational cohort evidence; wearable sleep metrics as risk markers, not diagnostics.",
  "cost": "",
  "reimbursement_status": "Not applicable.",
  "url": "https://doi.org/10.5665/sleep.2802",
  "notes": "PMID 23814339 (PMCID PMC3669060). Abstract loaded via NCBI E-utilities 2026-09-22. Mechanistic follow-up: sleep fragmentation linked to microglial aging in the same cohorts (PMID 31844665, Sci Adv 2019)."
 },
 {
  "id": "dh-syntermed-neuroq",
  "name": "NeuroQ 3.8 (PET/SPECT regional quantification)",
  "category": "AI-imaging",
  "developer": "Syntermed, Inc. (Atlanta)",
  "regulatory_status": "FDA-cleared",
  "clearance_date": "2018-08-16",
  "intended_use": "510(k) K180077 (KPS): ROI-count quantification of brain PET/SPECT (FDG, amyloid agents, SPECT perfusion, dopamine transporter) vs asymptomatic-control database to assist examination of scans acquired for neurodegenerative processes underlying cognitive and movement disorders (AD, Lewy body dementia and others named in indications). Earlier NeuroQ clearances K041022 (2004), K072307 (2008), K130451 (2013). Not machine-learning; statistical comparison to normal database.",
  "validated_population": "510(k) summary cites prior in-house/clinical validation from K041022/K072307 and a basal-ganglia (DaT) validation; dementia-specific validation cohort sizes not stated in loaded summary.",
  "published_accuracy": "FDA summary reports for the dopamine-transporter module: sensitivity, specificity and accuracy of quantification-based dichotomized interpretations all >=90%; inter-observer reproducibility r=0.59-0.78. No FDG/amyloid dementia accuracy figures in loaded summary; no peer-reviewed dementia validation loaded.",
  "evidence_strength": "Weak for dementia-specific claims from loaded sources (legacy quantification tool with long clinical use).",
  "cost": "",
  "reimbursement_status": "",
  "url": "https://www.accessdata.fda.gov/cdrh_docs/pdf18/K180077.pdf",
  "notes": "Source: FDA 510(k) summary K180077 loaded 2026-09-22; openFDA device/510k applicant Syntermed."
 }
]