Get help now — free helplines

You can call any of these for free. You do not need a diagnosis, an appointment, or a crisis to call — questions and plain exhaustion are reasons enough.

  • Alzheimer's Association 24/7 Helpline 800-272-3900 24 hours a day, 365 days a year Free, confidential support and information for people with dementia, caregivers, families and the public. Master's-level clinicians. Also Spanish.
  • 988 Suicide & Crisis Lifeline 988 24/7 Call or text 988, or chat at 988lifeline.org. For anyone in emotional distress or a mental-health crisis, including caregivers.
  • Alzheimer's Foundation of America (AFA) Helpline 866-232-8484 9:00 am - 9:00 pm ET, seven days a week Licensed social workers providing support, info and referrals. Also text message and web chat. Text: 646-586-5283

In a medical emergency, call 911. More numbers, and what each line does, on the help page.

Find studies

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.

Alzheimer's disease is a neurodegenerative disorder affecting millions globally, with early detection being critical for effective management. 2 key findings →

Evidence: low

Alzheimer's disease is a form of progressive dementia that significantly impacts the quality of life of patients and their families. 3 key findings →

Evidence: low

While this process allows machine learning models to make more precise and reliable diagnoses, systems developed on the basis of Dr. Roman Poznanski's DOT (Dynamic Optimization of Thought) theory offer a new method in the diagnosis of neurological diseases. 5 key findings →

Evidence: low

Overall, AI has substantial potential to support more precise, person-centred care for older adults, but realising this promise will require multimorbidity-aware, transparent models, robust evaluation in diverse geriatric populations and governance frameworks that ensure fairness, privacy and meaningful human oversight. 1 key finding →

Evidence: low

Alzheimer's disease (AD) is the most common type of dementia and represents a significant global health problem due to its profound impact on patients' quality of life and the heavy burden it places on health care. 1 key finding →

Evidence: low

The integration of artificial intelligence in medical image classification has significantly advanced disease detection. 2 key findings →

Evidence: low

Exploring Machine Learning Models to Uncover Pathways in ALS Pathogenesis Using Immunohistochemical Features

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. medRxiv (preprint) 2026-08-20

Hexanucleotide repeat expansions in C9orf72 are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia, yet the predictive information contained within associated inflammatory and proteinopathy markers remains incompletely characterised. 1 key finding →

Evidence: low

AbstractO_ST_ABSBackgroundC_ST_ABSGlucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 (SGLT2) inhibitors are increasingly used for type 2 diabetes. 5 key findings →

Participants: 6,328 Evidence: low

The feasibility criteria of >80% was met. 5 key findings →

Evidence: high

Neuropsychiatric symptoms (NPS) are increasingly recognized as critical components of the disease progression in Alzheimers disease (AD), yet their relationship with neurodegeneration remain poorly characterized. 2 key findings →

Participants: 1,756 Evidence: low

Alzheimers disease (AD) is characterized by substantial clinical and biological heterogeneity, with diverse neuroanatomical, cognitive, clinical, functional, and genetic risk profiles that are poorly captured by current diagnostic frameworks. 4 key findings →

Participants: 393 Evidence: low

Prior work suggests that perceived value may shape online support use, yet practical and trust-related barriers may still impede uptake even when beliefs are favorable. 5 key findings →

Design: cross-sectional Evidence: low

Predicting Conversion from SCD to MCI: A Machine Learning Study

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. medRxiv (preprint) 2026-09-08

BACKGROUNDSubjective cognitive decline (SCD) may precede mild cognitive impairment (MCI), but not all individuals with SCD progress to MCI. 5 key findings →

Design: longitudinal study Participants: 1,352 Evidence: moderate

Smartphone Passive Digital Phenotyping in Frontotemporal Lobar Degeneration

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 16 out of 100. medRxiv (preprint) 2026-09-21

IntroductionFrontotemporal lobar degeneration (FTLD) is a devastating disease that commonly results in early onset dementia, yet its rarity and heterogeneity limit large-scale research and clinical trials. 2 key findings →

Design: longitudinal study Participants: 567 Evidence: moderate

The Impact of Store-Based online Fulfilment on Grocery Retail Food Waste: An Empirical Analysis

⚠ Preprint — not yet peer-reviewed alzhub usefulness score 15 out of 100. Not indexed 2026

Problem Definition: Grocery retailers increasingly fulfil online orders from existing stores rather than from dark stores (dedicated warehouses/fulfilment centers). 3 key findings →

Evidence: low

Medicare and Medicaid provide health coverage to millions of Americans, including older adults, people with disabilities, low-income families, children, and individuals with complex medical and social needs. 1 key finding →

Evidence: low

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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.

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 27,380 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.

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 27,380 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 →

Newest studies, as a dated timeline →    Atom feed