27,380 Alzheimer's and dementia studies in plain English, each scored out of 100.
Across AD, ALS, and FTD, a convergent multimorbidity architecture centered on a shared metabolic and immune core was identified, accompanied by prominent neurobehavioral processes and intermediate systems including gastrointestinal, endocrine, hematological, hepatic, and sensory pathways. 5 key findings →
Evidence: low
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This paper presents a systematic bibliometric analysis of the research landscape at the intersection of Alzheimer's disease and gerontechnology, identifying key contributors, research hotspots, and emerging trends. 2 key findings →
Evidence: low
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Alzheimer's Disease (AD), the most prevalent dementia subtype, early detection is paramount for slowing disease progression because cures are not available. 2 key findings →
Participants: 115 Evidence: low
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A total of 83,807 articles were included for bibliometric analysis. 5 key findings →
Participants: 83,807 Evidence: low
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The use of linguistic biomarkers for detecting cognitive decline and early stages of dementia has demonstrated great potential due to its low-cost and non-invasive nature, especially towards a large aging population. 3 key findings →
Evidence: moderate
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Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia worldwide and is associated with substantial morbidity and mortality, including stroke, systemic embolism, heart failure, and dementia. 1 key finding →
Evidence: low
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Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. 5 key findings →
Evidence: low
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Overall, the application of ML to mental health has demonstrated a range of benefits across the areas of diagnosis, treatment and support, research, and clinical administration. 4 key findings →
Design: narrative review Evidence: low
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Finally, the most relevant features are selected by means of the non-parametric Mann- Whitney U-test. 2 key findings →
Evidence: low
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Artificial intelligence (AI) is rapidly expanding into dementia-related health and social care, with proposed applications ranging from early risk detection and monitoring to care coordination and service planning. 5 key findings →
Evidence: low
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Significant differences in 64% of engagement-related behaviors were found between groups, notably in torso movements, voice modulation, facial expressions, and concentration. 5 key findings →
Participants: 15 Evidence: low
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So far, we included 42 patients in our study, that were monitored for at least 7 consecutive days and nights, to form the largest database of its kind in the world. 5 key findings →
Participants: 42 Evidence: low
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AD patients exhibited a significantly higher prevalence of APOE e3/e4 and e4/e4 genotypes compared to DLB and HC (p <0.001). 5 key findings →
Evidence: low
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The calibration models for photopic lux and correlated color temperature demonstrated strong accuracy, with an adjusted R² of 0.858 and 0.982, respectively, ensuring reliable sensor measurements. 5 key findings →
Evidence: low
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Significant predictive performance was observed for several neurocognitive disorders. 5 key findings →
Evidence: low
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Dementia is a progressive condition that affects cognition, communication, mobility, and independence, posing growing challenges for individuals, caregivers, and healthcare systems. 5 key findings →
Evidence: low
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The smart device system to monitor tremors and to recognize its phenotypes for better outcomes of deep brain stimulation, applications evaluating fine motor functions, AI integrated electroencephalogram learning to diagnose epilepsy and psychological non-epileptic seizure, predict outcome of seizure surgeries, recognize patterns of autonomic instability to prevent sudden unexpected death in epilepsy (SUDEP), identify the pattern of complex algorithm in neuroimaging classifying cognitive impairment, differentiating and classifying concussion phenotypes, smartwatches monitoring atrial fibrillation to prevent strokes, and prediction of prognosis in dementia are unique examples of experimental utilizations of AI in the field of neurology. 1 key finding →
Evidence: low
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Telemedicine can improve access to speech and language evaluation services which is relevant to both dementia and other neurological diseases of the elderly. 4 key findings →
Evidence: low
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We used 1387 safety event reports for model development, 989 (71.3%) reports related to situational factors and 119 (8.6%) reports related to active failures. 5 key findings →
Evidence: low
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The CatBoost-based risk model achieved an area under the receiver-operating characteristic curve (AUROC) of 0.814 (<70 years) and 0.892 (<65 years). 5 key findings →
Evidence: low
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Three themes identified include (a) LOVOT's role in supporting engagement and stimulating conversation, (b) the irreplaceability of human touch and emotional nuances, and (c) concerns about ownership and equitable resource allocation. 4 key findings →
Evidence: low
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Random Forest achieves the highest accuracy of 97% on clinical data, while CNN achieves the best overall performance of 94% in MRI-based staging. 4 key findings →
Evidence: low
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Utilizing clinical data, the highest ROC AUC scores attained were 0.989, 0.927, and 0.907 for the identification of the CN, MCI, and dementia stages, respectively. 5 key findings →
Evidence: low
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Accurate and reproducible electroencephalography (EEG)-based classification of dementia remains a key challenge in computational neurodiagnostics. 4 key findings →
Evidence: low
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Dementia poses an on-going Canadian challenge due to an aging population, with cases projected to rise significantly by 2050. 4 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source Free full text
Free full text links and the Full text may need a subscription label come from Unpaywall, Europe PMC and OpenAlex records of free copies, checked 10 Oct 2026. A study with neither is unknown, not paywalled. Show only studies that are free to read
This is alzhub's own score. It is not an official metric, not an impact factor, and no journal, publisher or ranking body endorses it. We built it so that a reader who is not a scientist can tell a landmark trial from a conference abstract without having to already know the difference. Every point comes from one of 20 components, all of them printed on the study itself, so you can disagree with our arithmetic rather than having to trust the total.
Journals are placed in ordered tiers, never given a numeric impact factor — we could not verify current impact factors from a source we control, and an invented one would be worse than none. Tier 1 is the top-tier general journals (NEJM, The Lancet, JAMA, Nature, Science, Nature Medicine); tier 2 is the leading specialty journals; tier 3 is every other peer-reviewed journal. A separate part scores how much the journal's own papers are cited, which tells the tier-3 journals apart.
Two rules we don't bend. First, we never fill in a missing value: if a record does not state a sample size or a design, that component scores zero, and if we simply have no data for a part, such as a citation count, that part is left out and the study is scored on the parts we could check. The study card says which. Second, anything that is not a peer-reviewed article is capped at 16/100 and carries a warning chip — so a conference abstract or a company press release can never outrank a peer-reviewed paper, no matter how good it looks.
We rank a rigorous null result — a good trial showing that something does not work — above an early positive finding. Someone deciding whether to buy a supplement is served by that, and the rigour is already counted by the design and journal components.
The score is computed from the published data alone and is reproducible: the same file always yields the same numbers.
See the whole rubric drawn out → — four charts covering all 27,380 studies: how the scores are spread and where the cap bites, which of the 20 components the library is strong and weak on, which subjects rest on stronger evidence, and what kinds of study each subject is actually built from.
This is a large sample of the Alzheimer's literature, not an exhaustive index of it. It holds 27,380 records, built mostly from automated pulls of Europe PMC (60.6% of the library) and OpenAlex (18.6%), plus smaller pulls from PubMed, Crossref and medRxiv. If a study, a drug, or a finding isn't here, that is not evidence it doesn't exist in the literature — it may simply not have been pulled in yet.
1,032 records (3.8% of the library) are not peer-reviewed — 962 of those are preprints posted before any journal review, and the rest are conference abstracts, regulatory notices and reports. Every study card on this page states its status plainly, and the score above is capped for anything that isn't a peer-reviewed article.
See the full, machine-readable breakdown of this library's coverage →