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Research

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

Find studies

Showing 376–400 of 423 studies in Digital health tools · tagged Digital Tools (page 16 of 17) · 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.

Other 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.

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.

A modified α-synuclein seed amplification assay in Lewy body dementia using Raman spectroscopy and machine learning analysis

✓ Peer-reviewed alzhub usefulness score 36 out of 100. Journal of Neuroscience Methods 2025-11-15

Lewy body dementias (LBD), comprising dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD), are defined by misfolded α-synuclein aggregation. 1 key finding →

Evidence: low

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

Multimodal neuroimaging feature learning for multiclass diagnosis of Alzheimer's disease

✓ Peer-reviewed alzhub usefulness score 36 out of 100. IEEE transactions on bio-medical engineering 2014-11-20

The accurate diagnosis of Alzheimer's disease (AD) is essential for patient care and will be increasingly important as disease modifying agents become available, early in the course of the disease. 1 key finding →

Evidence: low

Full summary, score breakdown and related studies → Original source

Ensembles of Deep Learning Architectures for the Early Diagnosis of the Alzheimer's Disease

✓ Peer-reviewed alzhub usefulness score 36 out of 100. International journal of neural systems 2016-04-04

Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be simpler and more likely to be effective. 2 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source

Leveraging Artificial Intelligence in the Diagnosis of Neurodegenerative Disorders (Alzheimer's and Dementia) and in Managing Medication Schedules"

✓ Peer-reviewed alzhub usefulness score 35 out of 100. Damanhour Journal of Intelligent Systems and Informatics 2025-06-01

The Alzheimer's disease (AD) is recognized as one of the most common neurodegenerative causes of dementia worldwide, having been characterized by progressive cognitive decline for the most part. 2 key findings →

Participants: 461 Evidence: low

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

‘Machine Learning’ multiclassification for stage diagnosis of Alzheimer’s disease utilizing augmented blood gene expression and feature fusion

✓ Peer-reviewed alzhub usefulness score 35 out of 100. Discover Applied Sciences 2025-06-12

Three blood gene expression datasets of high dimensionality and low sample size (HDLSS) have been utilized in this study, with one dataset exhibiting significant class imbalance. 5 key findings →

Evidence: low

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

Identifying natural inhibitors against FUS protein in dementia through machine learning, molecular docking, and dynamics simulation

✓ Peer-reviewed alzhub usefulness score 34 out of 100. Frontiers in Neuroinformatics 2025-02-05

Dementia, a complex and debilitating spectrum of neurodegenerative diseases, presents a profound challenge in the quest for effective treatments. 5 key findings →

Evidence: low

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

Enhanced Multi-Model Machine Learning-Based Dementia Detection Using a Data Enrichment Framework: Leveraging the Blessing of Dimensionality

✓ Peer-reviewed alzhub usefulness score 34 out of 100. Bioengineering 2025-05-30

The early diagnosis of dementia, a progressive condition impairing memory, cognition, and functional ability in older adults, is essential for timely intervention and improved patient outcomes. 1 key finding →

Evidence: low

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

Enhanced in silico QSAR-based screening of butyrylcholinesterase inhibitors using multi-feature selection and machine learning

✓ Peer-reviewed alzhub usefulness score 34 out of 100. SAR and QSAR in environmental research 2025-02-01

Butyrylcholinesterase inhibition offers one of the formulated solutions to tackle the aggravating symptoms of dementia that downgrades to cholinergic neuronal loss in Alzheimer’s disease. 1 key finding →

Evidence: low

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

Artificial Intelligence and Personhood in Dementia

✓ Peer-reviewed alzhub usefulness score 33 out of 100. Dementia and Geriatric Cognitive Disorders 2025-08-20

The unprecedented rise of artificial intelligence (AI) in recent times is unparalleled in history.AI 1 seemingly possesses cognitive abilities that hitherto only humans could boast of -reason, an inimitable, embodied, and finite existence. 47Nonetheless, the ubiquitous abilities of AI can help to enhance treatment and care for PLWDs in 48 enabling early diagnosis, continuous monitoring and personalized support. 1 key finding →

Evidence: low

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

Agentic artificial intelligence in cognitive screening: A translational roadmap for dementia care

✓ Peer-reviewed alzhub usefulness score 33 out of 100. Journal of Alzheimer s Disease Reports 2025-01-01

Conventional dementia screening tools, whether paper tests or static artificial intelligence (AI) models, capture only a snapshot of cognition and need to be adminstered periodically. 5 key findings →

Evidence: low

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

Reimagining dementia screening: A stakeholder-informed perspective on artificial intelligence, digital biomarkers, and real-world implementation

✓ Peer-reviewed alzhub usefulness score 33 out of 100. Journal of Alzheimer s Disease Reports 2025-01-01

The approval of disease-modifying treatments for Alzheimer's disease demands a rethinking of cognitive screening. 4 key findings →

Evidence: low

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

Primary Care Physician Perspectives on Artificial Intelligence for Dementia Screening: A Qualitative Study

✓ Peer-reviewed alzhub usefulness score 33 out of 100. AJOB Empirical Bioethics 2026-01-02

Participants reported routine screening for cognitive impairment only in the context of the Medicare annual wellness visit and generally avoided routine screening because of limited treatment options to support patients, such as poor access to geriatrics/neuropsychiatric services. 5 key findings →

Evidence: low

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

Machine learning–enhanced screening funnel for clinical trials in Alzheimer's disease

✓ Peer-reviewed alzhub usefulness score 33 out of 100. Alzheimer s & Dementia Translational Research & Clinical Interventions 2025-04-01

This approach predicts clinical progression (2-year Clinical Dementia Rating Sum of Boxes change > 1) with an area under the curve of 0.836. 4 key findings →

Evidence: low

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

Emerging Trends in Early Dementia Diagnosis: An Analysis on Advanced Machine Learning Approaches

✓ Peer-reviewed alzhub usefulness score 32 out of 100. ACM Computing Surveys 2025-08-28

Dementia is the waning of cognitive abilities, which is typically seen with the natural aging process and includes issues with memory, language, and problem-solving abilities. 5 key findings →

Evidence: low

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

Digital Health Literacy and Physical Activity Programme for Improvement of Quality of Life in Caregivers of People with Dementia (CAREFIT): Study Protocol

✓ Peer-reviewed alzhub usefulness score 32 out of 100. Healthcare 2025-05-22

The proposed protocol for the CAREFIT programme represents an innovative and multidisciplinary initiative that leverages a digital platform to promote the well-being of informal caregivers of people with dementia. 3 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 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