Evidence map›Paper›PMID 40827296›Full record

ReviewInternational journal of ophthalmology2025

Deep learning applications for diabetic retinopathy and retinopathy of prematurity diseases diagnosis: a systematic review.

Elizabeth Ndunge Mutua, Bernard Shibwabo Kasamani, Christoph Reich

Abstract readReview
In one paragraph

Review in International journal of ophthalmology, 2025. 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. Article
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

3 authors.

Elizabeth Ndunge MutuaSchool of Computing & Engineering Sciences, Strathmore University, Nairobi 00100, Kenya.
Bernard Shibwabo KasamaniSchool of Computing & Engineering Sciences, Strathmore University, Nairobi 00100, Kenya.
Christoph ReichInstitute for Data Science, Cloud Computing and IT Security, Furtwangen University, Furtwangen 78120, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To review the existing deep learning applications for diagnosing diabetic retinopathy and retinopathy of prematurity diseases, the available public retinal databases for the diseases and apply the International Journal of Medical Informatics (IJMEDI) checklist were assessed the quality of included studies; an in-depth literature search in Scopus, Web of Science, IEEE and ACM databases targeting articles from inception up to 31

Indexed as

deep learningdiabetic retinopathyretinal databaseretinal vessel segmentationretinopathy of prematurity

Identifiers

PMID40827296
PMCPMC12311452

What OpenQuestion holds

Textmetadata
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.