The application and clinical translation of the self-evolving machine learning methods in predicting diabetic retinopathy and visualizing clinical transformation
The application of the self-evolving machine learning models can assist in identifying features associated with diabetic retinopathy in clinical settings, enabling early prediction of disease occurrence and aiding in the formulation of treatment plans to improve patient prognosis.
Authors
- Liqun Hu (ORCID: https://orcid.org/0009-0001-7026-906X)
- Siqing Zhang
- Binbin Li (ORCID: https://orcid.org/0000-0001-5825-129X)
- Wei Tang (ORCID: https://orcid.org/0000-0002-6351-4338)
- Shaojun Li (ORCID: https://orcid.org/0000-0002-3547-915X)
- Guishang Chen
Institutions
- Ganzhou People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Endocrinology
- Published
- 2024-09-19
- DOI
- https://doi.org/10.3389/fendo.2024.1429974
- Citations
- 3
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.21