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Research

27,380 Alzheimer's and dementia studies in plain English, each scored out of 100.

Find studies

Showing 401–425 of 1,109 studies · tagged Digital Tools (page 17 of 45) · 27,380 in the whole library · How the 0–100 score works

Browse by subject, author or institution

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

Subjects

Authors

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

Institutions

From OpenAlex; 12,859 studies have no institution on record and are not counted here.

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.

Vascular cognitive impairment and dementia: Prevention, treatments, mechanisms and management options for the future

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Neuropsychopharmacology 2026-01-19

Vascular Cognitive Impairment and Dementia (VCID), the second most common form of dementia, is becoming increasingly prevalent worldwide. 5 key findings →

Evidence: low

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

Comparison of Deep Learning and Traditional Machine Learning Models for Predicting Mild Cognitive Impairment Using Plasma Proteomic Biomarkers

✓ Peer-reviewed alzhub usefulness score 48 out of 100. International Journal of Molecular Sciences 2025-03-08

Mild cognitive impairment (MCI) is a clinical condition characterized by a decline in cognitive ability and progression of cognitive impairment. 3 key findings →

Participants: 239 Evidence: moderate

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

WMH ‐ DualTasker : A Weakly Supervised Deep Learning Model for Automated White Matter Hyperintensities Segmentation and Visual Rating Prediction

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Human Brain Mapping 2025-04-15

White matter hyperintensities (WMH) are neuroimaging markers linked to an elevated risk of cognitive decline. 2 key findings →

Participants: 60 Evidence: low

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

Effects of virtual reality-based cognitive training in older adults living without and with mild dementia: a pretest-posttest design pilot study

✓ Peer-reviewed alzhub usefulness score 48 out of 100. BMC research notes 2019-11-27

Older adults with mild dementia demonstrated worse baseline cognitive performance than participants without dementia. 4 key findings →

Participants: 72 Evidence: low

Full summary, score breakdown and related studies → Original source

Sharper in the morning: Cognitive time of day effects revealed with high-frequency smartphone testing

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Journal of clinical and experimental neuropsychology 2021-10-01

Decades of research has established a shift from an "eveningness" preference to a "morningness" preference with increasing age. 4 key findings →

Participants: 169 Evidence: low

Full summary, score breakdown and related studies → Original source

Digital cognitive assessments as low-burden markers for predicting future cognitive decline and tau accumulation across the Alzheimer's spectrum

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Alzheimer's & dementia : the journal of the Alzheimer's Association 2024-09-06

Digital assessments are effective at identifying at-risk individuals, supporting their utility as low-burden tools for early AD detection and monitoring. 2 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source

Deep Convolutional Neural Networks and Transfer Learning for Measuring Cognitive Impairment Using Eye-Tracking in a Distributed Tablet-Based Environment

✓ Peer-reviewed alzhub usefulness score 48 out of 100. IEEE transactions on bio-medical engineering 2020-12-21

This work demonstrates a mobile version of VisMET capable of estimating the presence of cognitive impairment. 1 key finding →

Participants: 250 Evidence: low

Full summary, score breakdown and related studies → Original source

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

Smartphone ownership and usage in Chinese- and English-speaking older adults

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Alzheimer's & dementia : the journal of the Alzheimer's Association 2021-12

33 Chinese- and 117 English-speaking older adults who received a diagnosis of normal cognition or mild cognitive impairment at consensus were included in the data analysis. 5 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source

The Functionality, Evidence, and Privacy Issues Around Smartphone Apps for the Top Neuropsychiatric Conditions

✓ Peer-reviewed alzhub usefulness score 48 out of 100. The Journal of neuropsychiatry and clinical neurosciences 2020-07-16

Eighty-three apps were reviewed (stroke, N=8; migraine, N=25; Alzheimer's disease and dementia, N=8; depression, N=7; anxiety, N=14; apps targeting depression and anxiety, N=21). 4 key findings →

Design: cross-sectional Evidence: low

Full summary, score breakdown and related studies → Original source

Smartphone applications for informal caregivers of chronically ill patients: a scoping review

✓ Peer-reviewed alzhub usefulness score 48 out of 100. NPJ digital medicine 2022-03-21

Mobile-health applications can be used to deliver timely and personalized health information to family and friends of chronically ill adults living in the community. 5 key findings →

Participants: 15 Evidence: low

Full summary, score breakdown and related studies → Original source

Microglial activation in the right amygdala-entorhinal-hippocampal complex is associated with preserved spatial learning in AppNL-G-F mice

✓ Peer-reviewed alzhub usefulness score 47 out of 100. NeuroImage 2020-12-29

Elevated microglial activation in the right amygdala-entorhinal-hippocampal complex of App NL-G-F mice is associated with better spatial learning. 5 key findings →

Design: cross-sectional Evidence: low

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

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

✓ Peer-reviewed alzhub usefulness score 47 out of 100. BMC research notes 2011-08-17

These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing. 3 key findings →

Evidence: low

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

A novel multi-modal machine learning based approach for automatic classification of EEG recordings in dementia

✓ Peer-reviewed alzhub usefulness score 47 out of 100. Neural networks : the official journal of the International Neural Network Society 2019-12-14

Electroencephalographic (EEG) recordings generate an electrical map of the human brain that are useful for clinical inspection of patients and in biomedical smart Internet-of-Things (IoT) and Brain-Computer Interface (BCI) applications. 1 key finding →

Evidence: low

Full summary, score breakdown and related studies → Original source Full text may need a subscription

Ethical concerns with the use of intelligent assistive technology: findings from a qualitative study with professional stakeholders

✓ Peer-reviewed alzhub usefulness score 47 out of 100. BMC medical ethics 2019-12-19

Our findings indicate a general agreement among professional stakeholders on the ethical promises and challenges raised by the use of IATs among older and disabled users. 4 key findings →

Evidence: low

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

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

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

Applications of artificial intelligence to aid early detection of dementia: A scoping review on current capabilities and future directions

✓ Peer-reviewed alzhub usefulness score 47 out of 100. Journal of biomedical informatics 2022-02-17

Seventy percent of cases are due to Alzheimer's disease (AD) pathology and there is a 10-20 year 'pre-clinical' period before significant cognitive decline occurs. 5 key findings →

Evidence: low

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

A Novel and Intelligent Home Monitoring System for Care Support of Elders with Cognitive Impairment

✓ Peer-reviewed alzhub usefulness score 47 out of 100. Journal of Alzheimer's disease : JAD 2016-10-01

It has been proved that the proposed system is suitable to support clinicians to reliably drive and evaluate clinical interventions toward quality of life improvement of people with cognitive impairment. 1 key finding →

Evidence: low

Full summary, score breakdown and related studies → Original source Full text may need a subscription

From across this tag

10 of the 1,102 studies in this tag, picked by a fixed rule (a hash of each study's address), not by score or date; each page of this list shows a different 10. The same 10 appear here every time.

↑ Change the filters

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 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.

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 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 →

Newest studies, as a dated timeline →    Atom feed