27,380 Alzheimer's and dementia studies in plain English, each scored out of 100.
Alzheimer’s Disease (AD) changes how the brain’s electrical activity behaves, and these changes can, in principle, be picked up directly from a resting-state EEG recording without any invasive testing. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
Resting-state EEG is a scalable modality for neurophysiological screening, but conventional spectral descriptors capture only part of the signal organization altered in neurodegenerative disease. 1 key finding →
Evidence: high
Full summary, score breakdown and related studies → Original source
Electroencephalography (EEG) records cortical activity with high temporal resolution without radiation and at low cost, which makes it a practical signal for automated screening of neurological disorders. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Artificial intelligence (AI) is now a credible translational research platform across the Alzheimer’s disease (AD) pathway, but its clinical value is often difficult to judge from performance metrics alone. 5 key findings →
Design: longitudinal study Evidence: moderate
Full summary, score breakdown and related studies → Original source
MCH-Guard offers a flexible clinical decision-support tool for optimizing spontaneous MCH & ARIA surveillance. 1 key finding →
Design: longitudinal study Participants: 813 Evidence: moderate
Full summary, score breakdown and related studies → Original source
We trained a self-configuring nnU-Net model for CMB segmentation in a hetero-geneous multicenter sample ( n =264), including 1.5T and 3T field strengths, SWI and T2*-GRE sequences, and community and clinical cohorts. 1 key finding →
Participants: 264 Evidence: low
Full summary, score breakdown and related studies → Original source
A bstract INTRODUCTION Treatment response in Alzheimer’s disease (AD) varies substantially across patients, yet no validated frameworks exist to estimate heterogeneous treatment effects (HTE) from observational data while controlling for confounding bias. 2 key findings →
Participants: 4,049 Evidence: low
Full summary, score breakdown and related studies → Original source
EcoXAI replaces monolithic AI text interfaces with an autonomous execution-driven framework with specialized bioinformatics agents for delivering proactive, data-driven insights grounded in established biological knowledge. 2 key findings →
Evidence: high
Full summary, score breakdown and related studies → Original source
Early, scalable detection of Alzheimer's disease (AD) and mild cognitive impairment (MCI) remains a global health priority, but non-invasive biomarkers that capture network-level dysfunction during standardized cognitive challenge remain limited. 1 key finding →
Participants: 13 Evidence: moderate
Full summary, score breakdown and related studies → Original source
By comparing these unsupervised representations to a depression-labelled source corpus, one cluster demonstrated mathematical proximity (measured via cosine similarity in a shared latent space) to the source depression centroid. 3 key findings →
Design: longitudinal study Evidence: moderate
Full summary, score breakdown and related studies → Original source
Precision psychiatry aims to identify biomarkers and develop prediction models to improve diagnosis, prognosis, and treatment selection. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
The ViTamyloid classifier achieved strong feature-separation metrics, yielding area under the receiver operating characteristic curve (AUROC) and precision-recall curve (AUPRC) values of 0.994/0.958 for CCP, 0.989/0.945 for CGP, 0.992/0.977 for CAA Type 1, and 0.997/0.978 for CAA Type 2. 4 key findings →
Design: longitudinal study Evidence: moderate
Full summary, score breakdown and related studies → Original source
Quantitative analysis of dendritic spine morphology is central to understanding synaptic function and its disruption in neurological disease, yet reliable measurement depends on accurate segmentation of spines from fluorescence microscopy images — a task still limited by faint or discontinuous spine necks and by tools that require extensive manual correction. 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
After more than three decades of intensive research, Alzheimer disease care remains largely palliative, and the field has drawn sustained criticism, both for that reason and for pursuing some directions of inquiry over others. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Symptom chronology emerged as a robust diagnostic discriminator, underscoring the clinical value of temporal disease trajectories. 3 key findings →
Participants: 932 Evidence: low
Full summary, score breakdown and related studies → Original source
Alzheimer’s disease (AD) is a neurodegenerative disorder that is characterized by structural changes of the hippocampus, thus hippocampal morphology becomes an important biomarker for early diagnosis. 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Multimodal integration of cognitive, neuroimaging, and polygenic data in the MHS-RWD tool yields strong discrimination for both early diagnosis of dementia and AD differential diagnosis. 2 key findings →
Participants: 1,100 Evidence: low
Full summary, score breakdown and related studies → Original source
Among 11,377 AD hospitalizations, 600 in-hospital deaths occurred (5.27%). 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Alzheimer’s disease (AD) target evidence is distributed across biological, chemical, structural, regulatory, and trial-registry sources, complicating reproducible target evaluation and modeling. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
To distinguish these cases, we trained three types of supervised 3D transformers (ViT3D, MINiT, NIT) and, as a non-collapsing alternative, a frozen self-supervised encoder (DINO), to classify people with dementia or mild cognitive impairment (MCI) versus cognitively normal (CN) individuals from 3D brain MRI, using data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). 2 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
A bstract Deep learning models for electroencephalography (EEG) pathology detection achieve competitive accuracy but offer limited interpretability. 5 key findings →
Evidence: low
Full summary, score breakdown and related studies → Original source
Alzheimer disease (AD) is a disorder of the nervous system that mostly impacts the brain cells and causes the slow destruction of the brain. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
Unlike traditional eager decision trees (eagerDT), which lacked sufficient training data for 17%-33% of patient profiles, lazyDT-MCCPath successfully modeled all profiles and achieved a 0.17 improvement in AUROC (0.66 vs. 0.83). lazyDT-MCCPath effectively translates pre-existing MCC profiles into personalized dementia risk probabilities for emerging conditions, which may help clinicians prioritize MCCs to monitor more closely. 1 key finding →
Evidence: low
Full summary, score breakdown and related studies → Original source
Machine learning (ML) methods have shown promise in modeling clinical trajectories associated with neurodegenerative disorders such as Alzheimer’s disease (AD). 3 key findings →
Design: longitudinal study Participants: 15,727 Evidence: moderate
Full summary, score breakdown and related studies → Original source
Neuroimaging studies that pool data across clinical sites often suffer from site effects — variability in imaging measures that arises from technical heterogeneity across sites as opposed to true biological signal. 5 key findings →
Design: longitudinal study Evidence: moderate
Full summary, score breakdown and related studies → Original source
10 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 10. The same 10 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 →