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Find studies

Showing 1,526–1,550 of 2,900 studies · tagged Brain Scans (page 62 of 116) · 27,780 in the whole library · How the 0–100 score works

Download bibliography of the first 500 of these 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.

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.

In vivo quantification of neurofibrillary tangles with [ 18 F]MK-6240

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Alzheimer's research & therapy 2018-07-31

This evaluation shows an [ 18 F]MK-6240 distribution in concordance with postmortem studies and that simplified quantitative approaches such as the SUVR offer valid estimates of neurofibrillary tangle load 90 min post injection. [ 18 F]MK-6240 is a promising tau tracer with the potential to be applied in the disease diagnosis and assessment of therapeutic interventions. 2 key findings →

Participants: 14 Evidence: low

Future longitudinal studies examining the association of more severe depressive symptoms and cerebral tau accumulation are needed to substantiate this finding and to guide prevention and treatment in AD. 4 key findings →

Design: cross-sectional Evidence: moderate

PET amyloid levels were consistent with sparse-to-no neuritic amyloid-β plaques in 51% of patients after 2 years of therapy. 3 key findings →

Design: clinical trial Participants: 89 Evidence: low

Progressive atrophy was revealed in presymptomatic individuals, with posterior cingulate and neocortical temporoparietal cortical losses, and medial temporal-lobe atrophy. 1 key finding →

Participants: 20 Evidence: low

A Deep Learning Model to Predict a Diagnosis of Alzheimer Disease by Using 18 F-FDG PET of the Brain

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Radiology 2018-11-06

By using fluorine 18 fluorodeoxyglucose PET of the brain, a deep learning algorithm developed for early prediction of Alzheimer disease achieved 82% specificity at 100% sensitivity, an average of 75.8 months prior to the final diagnosis. © RSNA, 2018 Online supplemental material is available for this article. 3 key findings →

Participants: 1,002 Evidence: low

We built and validated a deep learning algorithm predicting the individual diagnosis of Alzheimer's disease (AD) and mild cognitive impairment who will convert to AD (c-MCI) based on a single cross-sectional brain structural MRI scan. 5 key findings →

Design: cross-sectional Evidence: low

In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain diseases and predicting clinical scores using magnetic resonance imaging (MRI) have attracted increasing attention since these two tasks are highly correlated. 1 key finding →

Participants: 1,984 Evidence: low

Plasma p-tau217 was 57% higher in subjects with at least one APOE ε4 allele, increased with age, was higher in males, and negatively correlated with brain volume measures by magnetic resonance imaging. 4 key findings →

Evidence: low

Neurofilament light chain (NfL) is a marker of brain atrophy and predictor of disease progression in rare diseases such as Huntington Disease, but also in more common neurological disorders such as Alzheimer's disease. 5 key findings →

Participants: 62 Evidence: low

Postmortem brain studies of older drivers killed in car accidents indicate that many had Alzheimer disease (AD) neuropathologic changes. 2 key findings →

Participants: 129 Evidence: low

The novel tau-PET tracer [18F]PI-2620 detects the 3/4-repeat-(R)-tauopathy Alzheimer's disease (AD) and the 4R-tauopathies corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP). 2 key findings →

Participants: 29 Evidence: low

Atypical Alzheimer's disease phenotypes with normal or borderline PET biomarker profiles

✓ Peer-reviewed alzhub usefulness score 48 out of 100. Journal of neurology 2022-08-24

Posterior cortical atrophy (PCA) and logopenic progressive aphasia (LPA) are clinical syndromes that commonly have underlying Alzheimer's disease (AD), although non-AD pathologies have also been reported. 2 key findings →

Evidence: moderate

This study evaluated performance of a commercially available standardized software program for calculation of florbetapir PET standard uptake value ratios (SUVr) in comparison with an established research method. 1 key finding →

Participants: 183 Evidence: low

Positive correlations were found between eFBP/eFMM and 18F-FDG-PET SUVR independently of Aβ status and Aβ radiotracer (R>0.72, p<0.001). eFBP/eFMM single-subject analysis revealed clusters of significant hypoperfusion with good correspondence to hypometabolism topographies, independently of the underlying neurodegenerative patterns. 5 key findings →

Participants: 94 Evidence: low

In the 98 participants with long follow-up, Centiloid = 26 provided the highest overall predictive value = 87% (NPV = 85%, PPV = 88%). 5 key findings →

Participants: 37 Evidence: low

Classification of MCI and HC displayed highest accuracy based on diffusion MRI, which besides demonstrated high correlation with clinical scores. 5 key findings →

Participants: 26 Evidence: low

The disruption of functional connectivity is one of the early events that occurs in the brains of Alzheimer's disease (AD) patients. 2 key findings →

Participants: 32 Evidence: low

From across this tag

10 of the 2,885 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.

↑ Change the filters

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. Show only studies that are free to read

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 27,780 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 27,780 records, built mostly from automated pulls of Europe PMC (61.1% of the library) and OpenAlex (18.3%), 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 (3.7% 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