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Research

28,580 Alzheimer's and dementia studies in plain English, each scored out of 100.

Find studies

Showing 51–75 of 139 studies in Digital health tools · tagged Brain Scans (page 3 of 6) · 28,580 in the whole library · How the 0–100 score works

Download bibliography of these 139 studies, in this order: BibTeX (.bib) · RIS (.ris)

Browse by subject, author or institution

Each number is how many studies that link shows, with your other filters kept.

Other subjects

Authors

Names as each record prints them; the same person can appear under two spellings.

Institutions

From OpenAlex; 14,058 studies have no institution on record and are not counted here.

What “Digital health tools” covers

Digital health tools — Apps, wearables, online tests and other technology used to detect, monitor or support people with dementia.

A note on reading research. One study is rarely the final word.

We try to note the size of a study, whether it was in humans or animals, and how early-stage the finding is. If a summary here doesn't make that clear, treat it with extra caution and check the original source.

Neuropathology of White Matter Lesions, Blood-Brain Barrier Dysfunction, and Dementia

✓ Peer-reviewed alzhub usefulness score 50 out of 100. Stroke 2017-08-30

Our data suggest that some degree of blood-brain barrier dysfunction is common in older people and that this may be related to clinical dementia risk, additional to standard MRI biomarkers. 5 key findings →

Participants: 126 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

MRI and pathology of REM sleep behavior disorder in dementia with Lewy bodies

✓ Peer-reviewed alzhub usefulness score 50 out of 100. Neurology 2013-10-09

Patients with autopsy-confirmed low-, intermediate-, and high-likelihood DLB, according to the probability statement recommended by the third report of the DLB Consortium, and antemortem MRI, were identified (n = 75). 3 key findings →

Participants: 75 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Machine learning model for predicting Amyloid-β positivity and cognitive status using early-phase 18F-Florbetaben PET and clinical features

✓ Peer-reviewed alzhub usefulness score 50 out of 100. Scientific Reports 2025-07-01

This study developed machine learning models to predict Aβ positivity in Alzheimer’s disease by integrating early-phase 18 F-Florbetaben PET and clinical data to improve diagnostic accuracy. 2 key findings →

Participants: 176 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Reducing between scanner differences in multi-center PET studies

✓ Peer-reviewed alzhub usefulness score 49 out of 100. NeuroImage 2009-02-06

This work is part of the multi-center Alzheimer's Disease Neuroimaging Initiative (ADNI), a large multi-site study of dementia, including patients having mild cognitive impairment (MCI), probable Alzheimer's disease (AD), as well as healthy elderly controls. 5 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Automated MRI-based classification of primary progressive aphasia variants

✓ Peer-reviewed alzhub usefulness score 49 out of 100. NeuroImage 2009-06-06

Degeneration of language regions in the dominant hemisphere can result in primary progressive aphasia (PPA), a clinical syndrome characterized by progressive deficits in speech and/or language function. 4 key findings →

Participants: 86 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

MRI Characterizes the Progressive Course of AD and Predicts Conversion to Alzheimer's Dementia 24 Months Before Probable Diagnosis

✓ Peer-reviewed alzhub usefulness score 49 out of 100. Frontiers in aging neuroscience 2018-05-24

There is no disease-modifying treatment currently available for AD, one of the more impacting neurodegenerative diseases affecting more than 47.5 million people worldwide. 1 key finding →

Participants: 200 Evidence: moderate

Full summary, score breakdown and related studies → Original source Free full text

Multi-feature computational framework for combined signatures of dementia in underrepresented settings

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Journal of neural engineering 2022-08-25

The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. 5 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18 F-FDG PET of the Brain

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Radiology 2018-11-06

By using fluorine 18 fluorodeoxyglucose PET of the brain, a deep learning algorithm developed for early prediction of Alzheimer disease achieved 82% specificity at 100% sensitivity, an average of 75.8 months prior to the final diagnosis. © RSNA, 2018 Online supplemental material is available for this article. 3 key findings →

Participants: 1,002 Evidence: low

Full summary, score breakdown and related studies → Original source

Automated classification of Alzheimer's disease and mild cognitive impairment using a single MRI and deep neural networks

✓ Peer-reviewed alzhub usefulness score 48 out of 100. NeuroImage. Clinical 2018-12-18

We built and validated a deep learning algorithm predicting the individual diagnosis of Alzheimer's disease (AD) and mild cognitive impairment who will convert to AD (c-MCI) based on a single cross-sectional brain structural MRI scan. 5 key findings →

Design: cross-sectional Evidence: low

Full summary, score breakdown and related studies → Original source

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis

✓ Peer-reviewed alzhub usefulness score 48 out of 100. IEEE transactions on bio-medical engineering 2018-09-12

In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain diseases and predicting clinical scores using magnetic resonance imaging (MRI) have attracted increasing attention since these two tasks are highly correlated. 1 key finding →

Participants: 1,984 Evidence: low

Full summary, score breakdown and related studies → Original source

Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images from ADNI, AIBL, OASIS, and MIRIAD databases

✓ Peer-reviewed alzhub usefulness score 47 out of 100. Human brain mapping 2020-07-02

Biomarkers for dementia of Alzheimer's type (DAT) are sought to facilitate accurate prediction of the disease onset, ideally predating the onset of cognitive deterioration. 1 key finding →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Logopenic and nonfluent variants of primary progressive aphasia are differentiated by acoustic measures of speech production

✓ Peer-reviewed alzhub usefulness score 47 out of 100. PloS one 2014-02-28

Differentiation of logopenic (lvPPA) and nonfluent/agrammatic (nfvPPA) variants of Primary Progressive Aphasia is important yet remains challenging since it hinges on expert based evaluation of speech and language production. 3 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Identifying incipient dementia individuals using machine learning and amyloid imaging

✓ Peer-reviewed alzhub usefulness score 47 out of 100. Neurobiology of aging 2017-07-11

Identifying individuals destined to develop Alzheimer's dementia within time frames acceptable for clinical trials constitutes an important challenge to design studies to test emerging disease-modifying therapies. 5 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Cross-cohort generalizability of deep and conventional machine learning for MRI-based diagnosis and prediction of Alzheimer's disease

✓ Peer-reviewed alzhub usefulness score 47 out of 100. NeuroImage. Clinical 2021-06-04

This work validates the generalizability of MRI-based classification of Alzheimer's disease (AD) patients and controls (CN) to an external data set and to the task of prediction of conversion to AD in individuals with mild cognitive impairment (MCI). 2 key findings →

Participants: 199 Evidence: moderate

Full summary, score breakdown and related studies → Original source Free full text

Hereditary frontotemporal dementia is linked to chromosome 17q21-q22: a genetic and clinicopathological study of three Dutch families

✓ Peer-reviewed alzhub usefulness score 46 out of 100. Annals of neurology 1997-02-01

Hereditary frontotemporal dementia (HFTD) is a rare autosomal dominant form of presenile dementia characterized by behavioral changes and reduced speech. 2 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Cortical Thickness from MRI to Predict Conversion from Mild Cognitive Impairment to Dementia in Parkinson Disease: A Machine Learning-based Model

✓ Peer-reviewed alzhub usefulness score 46 out of 100. Radiology 2021-05-25

Cortical thickness from MRI helped predict conversion from mild cognitive impairment to dementia in Parkinson disease at an individual level, with improved performance when integrated with clinical variables. © RSNA, 2021 Online supplemental material is available for this article. 2 key findings →

Participants: 75 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Machine Learning-Based Framework for Differential Diagnosis Between Vascular Dementia and Alzheimer's Disease Using Structural MRI Features

✓ Peer-reviewed alzhub usefulness score 46 out of 100. Frontiers in neurology 2019-10-25

The experimental results demonstrate that the SVM with RBF achieved an encouraging performance with sensitivity (SEN), specificity (SPE), and accuracy (ACC) values of 82.65%, 87.17%, and 84.35%, respectively (AUC = 0.861, 95% CI = 0.820-0.902), for the differential diagnosis between VaD and AD. 2 key findings →

Participants: 93 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Rey's Auditory Verbal Learning Test scores can be predicted from whole brain MRI in Alzheimer's disease

✓ Peer-reviewed alzhub usefulness score 45 out of 100. NeuroImage. Clinical 2016-12-18

Rey's Auditory Verbal Learning Test (RAVLT) is a powerful neuropsychological tool for testing episodic memory, which is widely used for the cognitive assessment in dementia and pre-dementia conditions. 2 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

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Where “Free full text” comes from

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

How the 0–100 score works — and why some entries are capped

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.

  • Journal tier up to 10 pts
  • Journal's citation record up to 4 pts
  • Study design up to 12 pts
  • Strength of evidence up to 5 pts
  • Peer-review validation up to 10 pts
  • How recent up to 5 pts
  • Sample size up to 4 pts
  • Effect reported up to 3 pts
  • Studied in people up to 3 pts
  • Randomised / blinded up to 2 pts
  • Times cited up to 7 pts
  • Citations per year up to 5 pts
  • Impact for its field and year up to 6 pts
  • Cited by studies here up to 6 pts
  • Still being cited up to 4 pts
  • Senior author's track record up to 4 pts
  • Institution's track record up to 3 pts
  • Multi-centre collaboration up to 3 pts
  • Indexed in PubMed up to 2 pts
  • Free to read up to 2 pts

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 28,580 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.

What this library is — and isn't

This is a large sample of the Alzheimer's literature, not an exhaustive index of it. It holds 28,580 records, built mostly from automated pulls of Europe PMC (62.2% of the library) and OpenAlex (17.8%), 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.

1,034 records (3.6% 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 →

Newest studies, as a dated timeline →    Atom feed