27,380 Alzheimer's and dementia studies in plain English, each scored out of 100.
Standard univariate analysis of neuroimaging data has revealed a host of neuroanatomical and functional differences between healthy individuals and patients suffering a wide range of neurological and psychiatric disorders. 3 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Alzheimer's disease (AD). 3 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
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
Neurodegenerative disorders, such as Alzheimer's disease, are associated with changes in multiple neuroimaging and biological measures. 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Recently, there have been great interests for 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
There are growing numbers of studies using machine learning approaches to characterize patterns of anatomical difference discernible from neuroimaging data. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
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
Machine learning methods pool diverse information to perform computer-assisted diagnosis and predict future clinical decline. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Structural and functional brain images are playing an important role in helping us understand the changes associated with neurological disorders such as Alzheimer's disease (AD). 3 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Brain extraction is an important step in the analysis of brain images. 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Artificial intelligence can assist providers in a variety of patient care and intelligent health systems. 1 key finding →
Design: meta-analysis Evidence: high
Full summary, score breakdown and related studies → Original source
All three frameworks recognized biologically coherent AD-related signal despite differences in training cohort and assay methodology. 1 key finding →
Participants: 472 Evidence: moderate
Full summary, score breakdown and related studies → Original source
The analytic sample included 4,465 individuals (mean age 69.7±10.4 years; 58.7% female; 75.8% non-Hispanic White). 4 key findings →
Design: longitudinal study Participants: 51 Evidence: moderate
Full summary, score breakdown and related studies → Original source
The global burden of dementia is heavily concentrated in low- and middle-income countries (LMICs), yet biological diagnosis of Alzheimer’s Disease (AD) relies on positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis that are operationally inaccessible in these regions. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Dementia affects more than 55 million people worldwide, and its progressive decline is difficult to track using infrequent in-person assessments, which can miss subtle changes between visits and add to clinician burden. 2 key findings →
Design: cross-sectional Evidence: moderate
Full summary, score breakdown and related studies → Original source
Tau PET burden is associated with subsequent cognitive decline in Alzheimer's disease, motivating forecasts for monitoring and studies of spatially targeted therapies. 3 key findings →
Participants: 168 Evidence: low
Full summary, score breakdown and related studies → Original source
Alzheimer’s disease (AD) pathology develops years in advance prior to its clinical presentation. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Event-based models (EBMs) are used to infer ordering of biomarker alteration patterns with respect to disease progression. 1 key finding →
Design: longitudinal study Evidence: moderate
Full summary, score breakdown and related studies → Original source
Foundation models have driven major advancements in the language and vision domains, as seen in the popularity of Artificial Intelligence (AI) tools, and a growing number of studies are bringing the approach to human brain imaging. 2 key findings →
Participants: 343 Evidence: low
Full summary, score breakdown and related studies → Original source
A continuous amyloid staging score complements global amyloid burden for early AD staging and cognitive risk stratification. 2 key findings →
Design: longitudinal study Evidence: moderate
Full summary, score breakdown and related studies → Original source
Aging is the greatest risk factor for Alzheimer's disease (AD), yet how and when AD-related pathological progression diverges from aging remains poorly understood. 1 key finding →
Design: longitudinal study Evidence: moderate
Full summary, score breakdown and related studies → Original source
Semi-supervised multimodal fusion improves prediction and reveals interpretable imaging patterns that predict APOE4 and clinical diagnoses better than traditional approaches. 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Under nested cross-validation, the WWL kernel achieves a balanced accuracy of $0.651\pm0.028$, significantly outperforming both a raw-feature SVM and a histogram-based WL-kernel baseline. 3 key findings →
Evidence: moderate
Full summary, score breakdown and related studies → Original source
Alzheimer’s disease (AD) is a prevalent neurodegenerative disorder, and early diagnosis is essential for timely intervention. 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Accurate differential diagnosis between Alzheimer’s disease (AD) and frontotemporal dementia (FTD) is of critical importance for the early screening of neurodegenerative diseases. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
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
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 →