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

Elizabeth Ndunge Mutua. School of Computing & Engineering Sciences, Strathmore University, Nairobi 00100, Kenya. elizabeth.mutua@strathmore.edu

Affiliation:

Clc Number:

Fund Project:

Supported by DAAD, Google Research, and the Organization for Women in Science for the Developing World (OWSD).

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    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 31st January 2023 was done by two independent reviewers. In the review, 26 out of 1476 articles with a total of 36 models were included. Data size and model validation were found to be challenges for most studies. Deep learning models are gaining focus in the development of medical diagnosis tools and applications. However, there seems to be a critical issue with most of the studies being published, with some not including information about data sources and data sizes which is important for their performance verification.

    Reference
    Related
    Cited by
Get Citation

Elizabeth Ndunge Mutua, Bernard Shibwabo Kasamani, Christoph Reich. Deep learning applications for diabetic retinopathy and retinopathy of prematurity diseases diagnosis: a systematic review. Int J Ophthalmol, 2025,18(8):1594-1602

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
Publication History
  • Received:April 18,2024
  • Revised:April 09,2025
  • Adopted:
  • Online: July 18,2025
  • Published: