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Research

28,580 Alzheimer's and dementia studies in plain English, each scored out of 100.

Find studies

Showing 401–425 of 456 studies in Brain scans and imaging · free to read (page 17 of 19) · 28,580 in the whole library · How the 0–100 score works

Download bibliography of these 456 studies, in this order: BibTeX (.bib) · RIS (.ris)

Browse by subject, author or institution

Each number is how many studies that link shows, with your other filters kept.

Other subjects

Authors

Names as each record prints them; the same person can appear under two spellings.

Institutions

From OpenAlex; 14,058 studies have no institution on record and are not counted here.

What “Brain scans and imaging” covers

Brain scans and imaging — MRI, PET and other scans: what they show, how early, and how reliably.

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.

A Semiautomated Method for Quantification of F 18 Florbetapir PET Images

✓ Peer-reviewed alzhub usefulness score 39 out of 100. Journal of nuclear medicine : official publication, Society of Nuclear Medicine 2015-09-03

PET amyloid imaging is increasingly used in research trials related to Alzheimer disease and has potential as a quantitative biomarker. 1 key finding →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

EEG coherence reflects regional corpus callosum area in Alzheimer's disease

✓ Peer-reviewed alzhub usefulness score 39 out of 100. Journal of neurology, neurosurgery, and psychiatry 2005-01-01

Region specific correlations between corpus callosum size and EEG coherence suggest that the decline in interhemispheric connectivity in Alzheimer's disease results from a specific loss of cortical association neurones projecting through the corpus callosum. 3 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Longitudinal Structural MRI-Based Deep Learning And Radiomics Features For Predicting Alzheimer\\\\\\\'s Disease Progression

✓ Peer-reviewed alzhub usefulness score 39 out of 100. Zenodo (CERN European Organization for Nuclear Research) 2026-01-01

Alzheimer\\\'s disease (AD), the leading cause of dementia worldwide, affects more than 55 million individuals and gen-erates annual healthcare costs exceeding two trillion USD [14]. 5 key findings →

Design: longitudinal study Evidence: moderate

Full summary, score breakdown and related studies → Original source Free full text

Classifying mild cognitive impairment from normal cognition: fMRI complexity matches tau PET performance

✓ Peer-reviewed alzhub usefulness score 38 out of 100. Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring 2025-07-01

The fMRI entropy classifier matched the tau PET model in accuracy and outperformed it in F1 score (0.64 vs. 0.61) and area under the curve (AUC; 0.73 vs. 0.67). 4 key findings →

Evidence: moderate

Full summary, score breakdown and related studies → Original source Free full text

Alzheimer-typical temporo-parietal atrophy and hypoperfusion are associated with a more significant cholinergic impairment in amnestic neurodegenerative syndromes

✓ Peer-reviewed alzhub usefulness score 38 out of 100. Journal of Alzheimer s Disease 2025-03-21

BackgroundTo date, cholinomimetics remain central in the pharmacotherapy of Alzheimer's disease (AD) dementia. 2 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Deep Learning Framework for Characterizing Tau‐PET Spatial Heterogeneity along AD Spectrum: A Self‐supervised Approach

✓ Peer-reviewed alzhub usefulness score 37 out of 100. Alzheimer s & Dementia 2025-12-01

Three robustly differentiated AD subtypes (S1, S2, and S3) were identified, with 93% validation accuracy and Adjusted Mutual Information scores >0.89, each exhibiting distinct tau patterns. 5 key findings →

Design: cross-sectional Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Deep Learning Framework for Characterizing Tau‐PET Spatial Heterogeneity along AD Spectrum: A Self‐supervised Approach

✓ Peer-reviewed alzhub usefulness score 37 out of 100. Alzheimer s & Dementia 2025-12-01

Three robustly differentiated AD subtypes (S1, S2, and S3) were identified, with 93% validation accuracy and Adjusted Mutual Information scores >0.89, each exhibiting distinct tau patterns. 5 key findings →

Design: cross-sectional Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Dependency Grammar Approach to the Syntactic Complexity in the Discourse of Alzheimer Patients

✓ Peer-reviewed alzhub usefulness score 36 out of 100. Behavioral Sciences 2025-09-29

This study aims to investigate the syntactic complexity in individuals with Alzheimer's disease (AD) by conducting a comprehensive analysis that incorporates mean dependency distance (MDD), fine-grained grammatical metrics, and dependency network structures. 3 key findings →

Participants: 150 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Amyloid probability in Alzheimer disease from plasma, cerebrospinal fluid, and amyloid imaging

✓ Peer-reviewed alzhub usefulness score 36 out of 100. npj Dementia 2026-07-01

Blood-based biomarkers are increasingly used to triage patients for amyloid confirmation, yet performance is often reported versus a single comparator despite discordance between amyloid PET and CSF. 1 key finding →

Design: cross-sectional Participants: 320 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Progression-Aware and Explainable CNN–Transformer Framework for Multiclass Alzheimer’s Disease Staging Using MRI

✓ Peer-reviewed alzhub usefulness score 35 out of 100. Diagnostics 2026-02-16

The experimental findings on a multiclass MRI dataset of Alzheimer disease demonstrate consistent and high performance across cross-validation folds (mean F1-score (0.991 ± 0.003) and AUROC (0.9998 ± 0.0002)), without losing transparency and progress awareness. 2 key findings →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Blood-brain barrier permeability changes and neuroinflammation in Alzheimer disease progression

✓ Peer-reviewed alzhub usefulness score 35 out of 100. International Journal of Biology Sciences 2025-06-01

Roughly 32 million people worldwide live with Alzheimer disease, yet the vascular contributions to its progression remain incompletely mapped. 5 key findings →

Participants: 94 Evidence: moderate

Full summary, score breakdown and related studies → Original source Free full text

Multimodal Deep Learning for Dynamic and Static Neuroimaging: Integrating MRI and fMRI for Alzheimer Disease Analysis

✓ Peer-reviewed alzhub usefulness score 32 out of 100. Journal of Machine Learning for Modeling and Computing 2026-01-01

Magnetic Resonance Imaging (MRI) provides detailed structural information, while functional MRI (fMRI) captures temporal brain activity. 2 key findings →

Participants: 29 Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

Multi-domain synthetic medical image generation and dataset balancing with DGAN-WP-TL

✓ Peer-reviewed alzhub usefulness score 32 out of 100. Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization 2025-09-12

Imbalanced medical datasets significantly impair the performance of diagnostic models by biasing predictions towards majority classes. 1 key finding →

Evidence: low

Full summary, score breakdown and related studies → Original source Free full text

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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 28,580 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 28,580 records, built mostly from automated pulls of Europe PMC (62.2% of the library) and OpenAlex (17.8%), 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.

1,034 records (3.6% 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