27,380 Alzheimer's and dementia studies in plain English, each scored out of 100.
Retinal Optical Coherence Tomography (OCT) allows the non-invasive direct observation of the central nervous system, enabling the measurement and extraction of biomarkers from neural tissue that can be helpful in the assessment of ocular, systemic and Neurological Disorders (ND). 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Drug repurposing aims to find new uses for already existing and approved drugs. 3 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
In silico reuse of old drugs (also known as drug repositioning) to treat common and rare diseases is increasingly becoming an attractive proposition because it involves the use of de-risked drugs, with potentially lower overall development costs and shorter development timelines. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
Repositioning or repurposing drugs account for a substantial part of entering approval pipeline drugs, which indicates that drug repositioning has huge market potential and value. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
In this study, a drug repositioning algorithm based on a deep autoencoder and adaptive fusion was proposed to mitigate the problems of decreased precision and low-efficiency multisource data fusion caused by data sparseness. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
However, most existing research focuses on only a single modality of biomarkers for diagnosis of AD and MCI, although recent studies have shown that different biomarkers may provide complementary information for the diagnosis of AD and MCI. 4 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
For the last decade, it has been shown that neuroimaging can be a potential tool for the diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI), and also fusion of different modalities can further provide the complementary information to enhance diagnostic accuracy. 3 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Alzheimer's Disease (AD) is a multifactorial disease that shares common etiologies with its multiple comorbidities, especially vascular diseases. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
Accurately identifying the patients that have mild cognitive impairment (MCI) who will go on to develop Alzheimer's disease (AD) will become essential as new treatments will require identification of AD patients at earlier stages in the disease process. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
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
A new chaos-wavelet approach is presented for electroencephalogram (EEG)-based diagnosis of Alzheimer's disease (AD) employing a recently developed concept in graph theory, visibility graph (VG). 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
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
Accurate spatial normalization (SN) of amyloid positron emission tomography (PET) images for Alzheimer's disease assessment without coregistered anatomical magnetic resonance imaging (MRI) of the same individual is technically challenging. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
Using AI for dementia diagnosis is still in research stage, however some of the work points to the development of new medical devices. 4 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
In recent years, electroencephalography (EEG) has emerged as a low-cost, accessible and objective tools for the early diagnosis of Alzheimer's disease (AD). 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Brain age prediction is a machine learning method that estimates an individual's chronological age from their neuroimaging scans. 4 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
With the approval of aducanumab on the “Accelerated Approval Pathway” and the recognition of amyloid load as a surrogate marker, new successful therapeutic approaches will be driven by combination therapy as was the case in oncology after the launch of immune checkpoint inhibitors. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
EEG characteristics that correlate with the cognitive functions are important in detecting mild cognitive impairment (MCI) in T2DM. 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
In this study, we developed a network-based deep-learning approach, termed deepDR, for in silico drug repurposing by integrating 10 networks: one drug-disease, one drug-side-effect, one drug-target and seven drug-drug networks. 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Neuroimaging-based single subject prediction of brain disorders has gained increasing attention in recent years. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Overall, the application of ML to mental health has demonstrated a range of benefits across the areas of diagnosis, treatment and support, research, and clinical administration. 4 key findings →
Design: narrative review Evidence: low
Full summary, score breakdown and related studies → Original source
The accurate diagnosis of Alzheimer's disease (AD) and its early stage, i.e., mild cognitive impairment, is essential for timely treatment and possible delay of AD. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
The early identification of brain anatomy deviating from the normal pattern of growth and atrophy, such as in Alzheimer's disease (AD), has the potential to improve clinical outcomes through early intervention. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
Many machine learning and pattern classification methods have been applied to the diagnosis of Alzheimer's disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
This paper reviews recent progress in the diagnosis of Alzheimer's disease (AD) from electroencephalograms (EEG). 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
7 of the 205 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 7. The same 7 appear here every time.
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 →