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Research

28,180 Alzheimer's and dementia studies in plain English, each scored out of 100.

Find studies

Showing 326–350 of 423 studies in Digital health tools · tagged Digital Tools (page 14 of 17) · 28,180 in the whole library · How the 0–100 score works

Download bibliography of these 423 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; 13,658 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.

Neural basis of category-specific semantic deficits for living things: evidence from semantic dementia, HSVE and a neural network model

✓ Peer-reviewed alzhub usefulness score 40 out of 100. Brain : a journal of neurology 2007-04-01

Studies of patients with semantic impairments following brain damage offer key insights into the cognitive and neural organization of semantic memory. 1 key finding →

Evidence: low

Full summary, score breakdown and related studies → Original source

Deep learning-based feature representation for AD/MCI classification

✓ Peer-reviewed alzhub usefulness score 40 out of 100. Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention 2013-01-01

In recent years, there has been a great interest in computer-aided diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI). 5 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source

Interferon γ: a master cytokine in microglia-mediated neural network dysfunction and neurodegeneration

✓ Peer-reviewed alzhub usefulness score 40 out of 100. Trends in neurosciences 2022-10-22

Traditionally, lymphocytic interferon γ (IFN-γ) was considered to be a simple 'booster' of proinflammatory responses by microglia (brain-resident macrophages) during bacterial or viral infection. 2 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source

Multivariate data analysis and machine learning in Alzheimer's disease with a focus on structural magnetic resonance imaging

✓ Peer-reviewed alzhub usefulness score 40 out of 100. Journal of Alzheimer's disease : JAD 2014-01-01

Machine learning algorithms and multivariate data analysis methods have been widely utilized in the field of Alzheimer's disease (AD) research in recent years. 5 key findings →

Evidence: moderate

Full summary, score breakdown and related studies → Original source

Integrating spatial transcriptomics data across different conditions, technologies and developmental stages

✓ Peer-reviewed alzhub usefulness score 40 out of 100. Nature computational science 2023-10-12

With the rapid generation of spatial transcriptomics (ST) data, integrative analysis of multiple ST datasets from different conditions, technologies and developmental stages is becoming increasingly important. 5 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source

How technology is reshaping cognitive assessment: Lessons from the Framingham Heart Study

✓ Peer-reviewed alzhub usefulness score 39 out of 100. Neuropsychology 2017-11-01

Technological advances will catalyze groundbreaking discoveries for effective treatments of neurodegenerative cognitive disorders, such as AD, and inform novel strategies for dementia prevention and sustained lifelong cognitive health. 1 key finding →

Evidence: low

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

A review on omics-based biomarkers discovery for Alzheimer's disease from the bioinformatics perspectives: Statistical approach vs machine learning approach

✓ Peer-reviewed alzhub usefulness score 39 out of 100. Computers in biology and medicine 2021-10-14

Alzheimer's Disease (AD) is a neurodegenerative disease that affects cognition and is the most common cause of dementia in the elderly. 2 key findings →

Evidence: low

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

Evaluation of the Digital Alzheimer Center: Testing Usability and Usefulness of an Online Portal for Patients with Dementia and Their Carers

✓ Peer-reviewed alzhub usefulness score 39 out of 100. JMIR research protocols 2016-07-21

In the usability assessment, eight categories of errors were distinguished, of which three were of critical, two of medium, and three of low severity. 1 key finding →

Evidence: low

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

EEG-Based Dementia Classification Using CS-EMD Synchrony Features and Quantum Machine Learning

✓ Peer-reviewed alzhub usefulness score 39 out of 100. IEEE Transactions on Consumer Electronics 2025-03-05

Dementia is a condition that affects a very large population, and an effective clinical diagnosis can lead to early intervention to delay progressive cognitive decline. 2 key findings →

Evidence: low

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

Beneficial effect of artificial intelligence care call on memory and depression in community dwelling individuals with dementia

✓ Peer-reviewed alzhub usefulness score 39 out of 100. Scientific Reports 2025-07-25

Traditional dementia-prevention programs have limited accessibility and lack continuous monitoring, making sustained cognitive and emotional support challenging. 4 key findings →

Evidence: low

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

The role for artificial intelligence in identifying combination therapies for Alzheimer’s disease

✓ Peer-reviewed alzhub usefulness score 39 out of 100. The Journal of Prevention of Alzheimer s Disease 2025-10-27

Despite substantial investment in biomedical and pharmaceutical research over the past two decades, the global prevalence of Alzheimer's disease (AD) and AD-related dementias (AD/ADRD) is still rising. 1 key finding →

Evidence: low

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

Cornea Oculomics: A Clinical Blueprint for Extending Corneal Diagnostics and Artificial Intelligence in Systemic Health Insights

✓ Peer-reviewed alzhub usefulness score 39 out of 100. Diagnostics 2025-03-06

Oculomics is an emerging field that leverages ophthalmic imaging data to identify biomarkers of systemic disease, facilitating early diagnosis and risk stratification. 5 key findings →

Evidence: low

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

Human-Centered Ambient and Wearable Sensing for Automated Monitoring in Dementia Care: A Scoping Review

✓ Peer-reviewed alzhub usefulness score 39 out of 100. IEEE Internet of Things Journal 2026-01-22

We conducted a scoping review to map the rapidly evolving landscape of wearable and ambient sensing technologies for monitoring people with dementia across home and institutional settings. 4 key findings →

Evidence: low

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

Older Adults' Reasons for Using Technology while Aging in Place

✓ Peer-reviewed alzhub usefulness score 39 out of 100. Gerontology 2015-06-04

The level of technology use in the context of aging in place is influenced by six major themes: challenges in the domain of independent living; behavioral options; personal thoughts on technology use; influence of the social network; influence of organizations, and the role of the physical environment. 4 key findings →

Evidence: low

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

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia

✓ Peer-reviewed alzhub usefulness score 38 out of 100. Neuroinformatics 2016-07-01

We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. 5 key findings →

Evidence: low

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

Integrative and interpretable framework to unveil the neurophysiological fingerprint of Alzheimer’s disease and mild cognitive impairment: A machine learning-SHAP approach

✓ Peer-reviewed alzhub usefulness score 38 out of 100. Journal of Applied Biomedicine 2025-06-13

Dementia and mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) are neurological pathologies associated with disruptions in brain electromagnetic activity, typically studied using magnetoencephalography (MEG) and electroencephalography (EEG). 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 28,180 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 28,180 records, built mostly from automated pulls of Europe PMC (61.7% of the library) and OpenAlex (18.1%), 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 (3.7% 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