27,380 Alzheimer's and dementia studies in plain English, each scored out of 100.
We conducted a systematic review of research in artificial intelligence (AI) for retinal fundus photographic images. 2 key findings →
Design: systematic review Evidence: high
Full summary, score breakdown and related studies → Original source Free full text
Early identification of individuals at risk of developing Alzheimer's disease (AD) dementia is important for developing disease-modifying therapies. 4 key findings →
Design: cross-sectional Participants: 1,677 Evidence: moderate
Full summary, score breakdown and related studies → Original source Free full text
After removal of duplicates, our initial search returned 3955 records. 3 key findings →
Evidence: high
Full summary, score breakdown and related studies → Original source Free full text
Online education involving a celebrity may be an effective strategy for educating college students about AD risk reduction strategies. 1 key finding →
Design: randomized controlled trial Participants: 721 Evidence: high
Full summary, score breakdown and related studies → Original source Free full text
PARO may have some effect on motor activity of older people with dementia in long-term care, but not on sleep patterns. 2 key findings →
Design: randomized controlled trial Evidence: high
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Forty-eight studies from 18,456 screened abstracts (Dementia: n = 2,516, Control: n = 1,224) met inclusion criteria for the systematic review. 5 key findings →
Design: systematic review Participants: 2,516 Evidence: high
Full summary, score breakdown and related studies → Original source Free full text
Due to the growing number of older adults with cognitive impairment, it is essential to delay the onset and progression of cognitive decline and promote a healthy lifestyle. 1 key finding →
Design: systematic review Evidence: high
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Amyloid protein precursor (APP), presenilin-1 (PSEN1), and presenilin-2 (PSEN2) mutations cause autosomal dominant forms of early-onset Alzheimer disease (AD-EOAD). 4 key findings →
Participants: 170 Evidence: low
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In the prospective GLORIA-AF registry of AF patients, the presence of clinical complexity was associated with lower odds of being prescribed with OAC (odds ratio [OR] 0.50, 95% confidence interval [CI] 0.44–0.57), higher OAC discontinuation, and with a higher risk of adverse events (hazard ratio [HR] 1.63, 95% CI 1.43–1.86).[ 4 ] Indeed, “high clinical complexity” patients defined using latent class analysis constituted 6.6% of AF patients, and was associated with higher hazards of experiencing the primary composite outcome of all-cause death and major adverse cardiovascular events (HR 1.47, 95% 1.24–1.75).[ 5 ] Comorbidities and polypharmacy have an important influence on decision-making, by conditioning either lack of prescription of OAC in patients at risk or inappropriate dosing.[ 6 ] [ 7 ] [ 8 ] Recognizing that AF management is more than simply OAC alone, and requires a holistic and integrated care approach, contemporary guidelines globally on AF management have promoted this concept, based on the Atrial fibrillation Better Care (ABC) pathway, emphasizing Anticoagulation, Better symptom management with rate or rhythm control, and Comorbidity/lifestyle management.[ 9 ] [ 10 ] [ 11 ] The ABC pathway is well supported by clinical trial and real-world evidence,[ 11 ] whereby adherence to the ABC pathway is associated with a reduction in all-cause and cardiovascular mortality, stroke, and bleeding.[ 12 ] [ 13 ] Despite this, adherence to ABC-based management remains low, whereby a meta-analysis of 14 studies revealed that only 21% (95% CI 13–34%) of AF patients were managed in accordance with the ABC pathway.[ 12 ] This perhaps highlights a critical gap in the implementation of comprehensive evidence-based care strategies. 2 key findings →
Design: meta-analysis Evidence: high
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This paper explores the rationale for a mobile phone-led intervention and details the app's effect on behavior change and subsequent clinical outcomes. 5 key findings →
Design: randomized controlled trial Participants: 102 Evidence: high
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Alzheimer's disease is the primary cause of dementia worldwide, with an increasing morbidity burden that may outstrip diagnosis and management capacity as the population ages. 5 key findings →
Participants: 417 Evidence: low
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Early diagnosis of cognitive disorders in older adults is a major healthcare priority with benefits to patients, families, and health systems. 1 key finding →
Design: systematic review Evidence: high
Full summary, score breakdown and related studies → Original source Free full text
Supervised intervention delivery is linked to greatest benefits. 2 key findings →
Design: meta-analysis Evidence: high
Full summary, score breakdown and related studies → Original source Free full text
Mild cognitive impairment (MCI) is often considered an early stage of dementia, with estimated rates of progression to dementia up to 80-90% after approximately 6 years from the initial diagnosis. 2 key findings →
Design: systematic review Evidence: high
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Comorbid cardiovascular and metabolic risk factors (CVM) differentially impact brain structure and increase dementia risk, but their specific magnetic resonance imaging signatures (MRI) remain poorly characterized. 1 key finding →
Design: cohort study Participants: 37,096 Evidence: moderate
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Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully provided automated solutions to numerous real-world problems. 1 key finding →
Evidence: low
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Both interventions were highly feasible and acceptable and allowed improvement in different aspects of cognitive and psychosocial functioning in MCI subjects. 4 key findings →
Evidence: high
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The study consists of 25,186 patients (mean age = 63.0, interquartile range [IQR] of age = 15.1 years, male = 50%). 3 key findings →
Design: cohort study Participants: 25,186 Evidence: moderate
Full summary, score breakdown and related studies → Original source Free full text
To develop a new method for measuring Alzheimer's disease (AD)-specific similarity of cortical atrophy patterns at the individual-level, we employed an individual-level machine learning algorithm. 5 key findings →
Design: longitudinal study Participants: 473 Evidence: moderate
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The most novel characteristics of our machine learning model compared to previous ones are the following: 1) our deep learning model is multi-tasking, in the sense that it jointly learns to simultaneously predict both MCI to AD conversion as well as AD vs. healthy controls classification, which facilitates relevant feature extraction for AD prognostication; 2) the neural network classifier employs fewer parameters than other deep learning architectures which significantly limits data-overfitting (we use ∼550,000 network parameters, which is orders of magnitude lower than other network designs); 3) both structural MRI images and their warp field characteristics, which quantify local volumetric changes in relation to the MRI template, were used as separate input streams to extract as much information as possible from the MRI data. 1 key finding →
Participants: 785 Evidence: low
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NULISA plasma biomarkers revealed disease-specific protein patterns. 5 key findings →
Design: systematic review Participants: 194 Evidence: high
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Our study demonstrates that MRI, a widespread imaging technology, can individually identify bvFTD with high accuracy in multi-center imaging data, paving the road to personalized diagnostic approaches in the future. 2 key findings →
Design: meta-analysis Evidence: high
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There is increasing interest in the use of technology to support social health in dementia. 5 key findings →
Design: systematic review Evidence: high
Full summary, score breakdown and related studies → Original source Free full text
This study included 54 articles, comprising 14,446 participants from 10 countries. 5 key findings →
Design: randomized controlled trial Participants: 54 Evidence: high
Full summary, score breakdown and related studies → Original source Free full text
The effects on depression and other outcomes were consistent with those observed for in-person programs, suggesting the viability of well-designed automated intervention. 2 key findings →
Design: RCT Participants: 274 Evidence: moderate
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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.
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.
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.
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 →