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Research

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

Find studies

Showing 151–175 of 571 studies · free to read · tagged Digital Tools (page 7 of 23) · 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.

Digital technologies as biomarkers, clinical outcomes assessment, and recruitment tools in Alzheimer's disease clinical trials

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Alzheimer's & dementia (New York, N. Y.) 2018-05-24

Digital technology is transforming the development of drugs for Alzheimer's disease and was the topic of the Alzheimer's Association's Research Roundtable on its May 23-24, 2017 meeting. 1 key finding →

Evidence: low

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

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Translational research : the journal of laboratory and clinical medicine 2018-01-10

Alzheimer's disease (AD) is a major neurodegenerative disease and the most common cause of dementia. 5 key findings →

Design: longitudinal study Evidence: moderate

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

Modifiable risk factors for dementia and dementia risk profiling. A user manual for Brain Health Services-part 2 of 6

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Alzheimer's research & therapy 2021-10-11

Rare variants should only be investigated in users with a family history of early-onset dementia in a first degree relative. 5 key findings →

Evidence: low

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

A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Frontiers in neurology 2019-07-16

The final algorithm demonstrated an AUROC of 0.88, sensitivity of 77.7%, and a specificity of 79.9% on excluded test data. 4 key findings →

Evidence: low

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

Facing the digital divide into a dementia clinic during COVID-19 pandemic: caregiver age matters

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology 2021-01-18

The most impacting factors on digital divide in our population are the social support networks and the experience with the technology: the presence of a digital native caregiver. 2 key findings →

Participants: 34 Evidence: low

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

Increased Diagnostic Accuracy of Digital vs. Conventional Clock Drawing Test for Discrimination of Patients in the Early Course of Alzheimer's Disease from Cognitively Healthy Individuals

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Frontiers in aging neuroscience 2017-04-11

The conventional Clock Drawing Test (cCDT) is a rapid and inexpensive screening tool for detection of moderate and severe dementia. 4 key findings →

Participants: 20 Evidence: low

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

Differences in cohort study data affect external validation of artificial intelligence models for predictive diagnostics of dementia - lessons for translation into clinical practice

✓ Peer-reviewed alzhub usefulness score 51 out of 100. The EPMA journal 2020-06-22

Artificial intelligence (AI) approaches pose a great opportunity for individualized, pre-symptomatic disease diagnosis which plays a key role in the context of personalized, predictive, and finally preventive medicine (PPPM). 5 key findings →

Design: cohort study Evidence: moderate

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

Exploiting machine learning models to identify novel Alzheimer's disease biomarkers and potential targets

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Scientific reports 2023-03-27

We still do not have an effective treatment for Alzheimer's disease (AD) despite it being the most common cause of dementia and impaired cognitive function. 1 key finding →

Evidence: low

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

Exploring the Effectiveness of Machine Learning and Deep Learning Techniques for EEG Signal Classification in Neurological Disorders

✓ Peer-reviewed alzhub usefulness score 51 out of 100. IEEE Access 2025-01-01

Neurological disorders are among the leading causes of both physical and cognitive disabilities worldwide, affecting approximately 15% of the global population. 4 key findings →

Evidence: low

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

Retinal biomarkers in cognitive impairment and dementia: Structural, functional, and molecular insights

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Alzheimer s & Dementia 2025-09-01

Cognitive impairment and dementia, including Alzheimer's disease (AD), pose a global health crisis, necessitating non-invasive biomarkers for early detection. 1 key finding →

Design: longitudinal study Evidence: moderate

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

An AI‐first framework for multimodal data in Alzheimer's disease and related dementias

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Alzheimer s & Dementia 2025-09-01

Advancing the understanding and management of Alzheimer's disease and related dementias requires integrating and analyzing diverse data modalities. 5 key findings →

Design: longitudinal study Evidence: moderate

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

Diagnostic performance of actigraphy in Alzheimer’s disease using a machine learning classifier – a cross-sectional memory clinic study

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Alzheimer s Research & Therapy 2025-05-21

Actigraphy accurately identifies different dementia etiologies and could serve as a supplement to diagnostic investigations in patients with suspected AD for differential diagnostic purposes. 1 key finding →

Design: cross-sectional Participants: 29 Evidence: low

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

Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learning

✓ Peer-reviewed alzhub usefulness score 51 out of 100. GeroScience 2025-04-26

Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer's disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. 5 key findings →

Design: cross-sectional Participants: 568 Evidence: moderate

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

Generative artificial intelligence in dementia care: a scoping review protocol on nursing roles, experiences and ethical perspectives

✓ Peer-reviewed alzhub usefulness score 51 out of 100. BMJ Open 2026-02-01

Critical appraisal will not be undertaken, as it is optional in scoping reviews and is not aligned with the primary mapping objectives of this review. 5 key findings →

Design: meta-analysis Evidence: high

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

Enhancing Dementia Risk Prediction with Heart Rate and Machine Learning in the Canadian Longitudinal Study on Aging (CLSA)

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Alzheimer s & Dementia 2025-12-01

Among the 18,013 participants with complete data for analysis, 516 (2.86%) exhibited cognitive impairment. 5 key findings →

Design: longitudinal study Participants: 27,768 Evidence: moderate

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

A machine learning-based approach to predict depression in Chinese older adults with subjective cognitive decline: a longitudinal study

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Scientific Reports 2025-07-24

This study aims to identify depressive risks in elderly individuals with subjective cognitive decline (SCD) and develop a predictive model using machine learning algorithms to enable timely interventions. 3 key findings →

Design: longitudinal study Evidence: moderate

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

Diabetic retinopathy as the primary predictor of mild cognitive impairment in type 2 diabetes: Insights from machine learning models

✓ Peer-reviewed alzhub usefulness score 51 out of 100. PLoS ONE 2025-09-26

Mild cognitive impairment (MCI) is a significant and increasingly recognized problem in individuals with type 2 diabetes mellitus (T2DM). 2 key findings →

Design: prospective cohort Participants: 100 Evidence: moderate

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

AI-powered model for accurate prediction of MCI-to-AD progression

✓ Peer-reviewed alzhub usefulness score 51 out of 100. Acta Pharmaceutica Sinica B 2025-02-10

Alzheimer's disease (AD) remains a formidable challenge in modern healthcare, necessitating innovative approaches for its early detection and intervention. 2 key findings →

Design: longitudinal study Evidence: moderate

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

Insights into Systemic Disease through Retinal Imaging-Based Oculomics

✓ Peer-reviewed alzhub usefulness score 50 out of 100. Translational vision science & technology 2020-02-12

Among the most noteworthy developments in ophthalmology over the last decade has been the emergence of quantifiable high-resolution imaging modalities, which are typically non-invasive, rapid and widely available. 1 key finding →

Evidence: low

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

↑ 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.

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