Evidence map›Paper›PMID 42165286›Full record

ArticleThe Cochrane database of systematic reviews2026

Artificial intelligence for detection and staging of Alzheimer's disease using retinal images.

Meet Panjwani, Jonathan M Holmes, Su-Hsun Liu, Eungjoo Lee, Steven Rapcsak, Abel Harris, Igor Kozak

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The Cochrane database of systematic reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Meet PanjwaniDepartment of Ophthalmology and Vision Science, University of Arizona, Tucson, Arizona, USA.ORCID 0009-0008-8782-5393
Jonathan M HolmesDepartment of Ophthalmology and Vision Science, University of Arizona, Tucson, Arizona, USA.
Su-Hsun LiuDepartment of Ophthalmology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
Eungjoo LeeDepartment of Electrical and Computer Engineering, University of Arizona, Tucson, USA.
Steven RapcsakDepartment of Neurology, University of Arizona, Tucson, Arizona, USA.
Abel HarrisCollege of Medicine, University of Arizona College of Medicine-Tucson, Tucson, Arizona, USA.
Igor KozakDepartment of Ophthalmology and Vision Science, University of Arizona, Tucson, Arizona, USA.

Funding

Maximizing Use of High-Quality Evidence in Eye Care: Cochrane Eyes and Vision US ProjectUG1EY020522 · NEI · UNIVERSITY OF COLORADO DENVER · PI Tianjing Li · 2017 to 2026
$10.1M
NEI NIH HHS UG1 EY020522
6 · The paper itself

Abstract

objectivesThis is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To determine the diagnostic accuracy of AI algorithm-based retinal image reading for detecting referral-requiring Alzheimer's disease in adults who have behavioral symptoms or cognitive decline in the primary care setting. Secondary objectives Where data are available, we will investigate heterogeneity by incorporating covariates in a metaregression.

Indexed as

Alzheimer DiseaseArtificial IntelligenceRetinaAlgorithmsHumansResearch DesignSystematic Reviews as Topic

Identifiers

PMID42165286
PMCPMC13191722

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.