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Find studies

Showing 326–350 of 1,116 studies · tagged Digital Tools (page 14 of 45) · 27,780 in the whole library · How the 0–100 score works

Download bibliography of the first 500 of these 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.

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.

The high failure rate of clinical trials in Alzheimer's disease (AD) and AD-related dementia (ADRD) is due to a lack of understanding of the pathophysiology of disease, and this deficit may be addressed by applying artificial intelligence (AI) to "big data" to rapidly and effectively expand therapeutic development efforts. 5 key findings →

Evidence: low

The dCDT is able to operationally define graphomotor output that cannot be measured using traditional paper and pencil test administration in older health controls and participants with dementia. 4 key findings →

Participants: 175 Evidence: low

The aggregation of Aβ42-peptides and the formation of drusen in age-related macular degeneration (AMD) are due in part to the inability of homeostatic phagocytic mechanisms to clear self-aggregating Aβ42-peptides from the extracellular space. 4 key findings →

Evidence: low

Social robots in advanced dementia

✓ Peer-reviewed alzhub usefulness score 50 out of 100. Frontiers in aging neuroscience 2015-09-03

Pilot studies applying a humanoid robot (NAO), a pet robot (PARO) and a real animal (DOG) in therapy sessions of patients with dementia in a nursing home and a day care center. 4 key findings →

Design: clinical trial Participants: 101 Evidence: low

The AI-powered pipeline achieved robust performance with intraclass correlation coefficients exceeding 0.97 for regional uptake estimation compared with MR-based ground truth. 5 key findings →

Design: longitudinal study Participants: 666 Evidence: moderate

Our findings indicate that using location-based trajectory metrics with clinical measures significantly improves the predictability of motor agitation beyond individual baselines. 5 key findings →

Design: longitudinal study Evidence: moderate

Integrative machine learning approach to risk prediction for dementia and Alzheimer’s disease

✓ Peer-reviewed alzhub usefulness score 50 out of 100. GeroScience 2025-08-27

Dementia, particularly Alzheimer's disease (AD), presents a growing global health challenge characterized by cognitive decline, behavioral changes, and loss of independence. 1 key finding →

Participants: 2,878 Evidence: moderate

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

Isolated rapid eye movement sleep behavior disorder (iRBD) is a major prodromal marker of α-synucleinopathies, often preceding the clinical onset of Parkinson's disease, dementia with Lewy bodies, or multiple system atrophy. 3 key findings →

Participants: 31 Evidence: moderate

Sensitivity and False Alarm Rate of a Fall Sensor in Long-Term Fall Detection in the Elderly

✓ Peer-reviewed alzhub usefulness score 50 out of 100. Gerontology 2014-08-13

The fall detection system detected 12 out of 15 real-life falls, having a sensitivity of 80.0%, with a false alarm rate of 0.049 alarms per usage hour with the implemented real-time system. 3 key findings →

Participants: 15,500 Evidence: low

Overall, the results suggest that ARC is reliable and valid and represents a feasible tool for assessing cognitive changes associated with the earliest stages of AD. 4 key findings →

Participants: 22 Evidence: low

Repeated smartphone-assisted cognitive testing is feasible with reasonable adherence and moderate relative validity for the Stroop and the Trail Making tests compared with conventional neuropsychological tests. 3 key findings →

Participants: 151 Evidence: low

We found patient and care partner input to be critical throughout the development process for early identification of design and usability issues and for identifying solutions not previously considered by our research team. 2 key findings →

Participants: 13 Evidence: low

BrainCheck was able to distinguish between diagnoses of dementia, MCI, and NC, providing a potentially reliable tool for early detection of cognitive impairment. 1 key finding →

Participants: 99 Evidence: low

Although there were no significant changes in caregiver burden, we were encouraged by the increased emotional well-being of our participants following the completion of our program. 4 key findings →

Participants: 21 Evidence: low

From across this tag

10 of the 1,109 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 27,780 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 27,780 records, built mostly from automated pulls of Europe PMC (61.1% of the library) and OpenAlex (18.3%), 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