This paper is in the following e-collection/theme issue:

Machine Learning (2001) Diabetes (251) Diabetic Retinopathy (16) Tools, Programs and Algorithms (366)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58107, first published .
Development and Validation of a Machine Learning Algorithm for Predicting Diabetes Retinopathy in Patients With Type 2 Diabetes: Algorithm Development Study

Development and Validation of a Machine Learning Algorithm for Predicting Diabetes Retinopathy in Patients With Type 2 Diabetes: Algorithm Development Study

Development and Validation of a Machine Learning Algorithm for Predicting Diabetes Retinopathy in Patients With Type 2 Diabetes: Algorithm Development Study

Authors of this article:

Sunyoung Kim1, 2 Author Orcid Image ;   Jaeyu Park2, 3 Author Orcid Image ;   Yejun Son2, 4 Author Orcid Image ;   Hojae Lee2, 3 Author Orcid Image ;   Selin Woo2 Author Orcid Image ;   Myeongcheol Lee2, 3 Author Orcid Image ;   Hayeon Lee2 Author Orcid Image ;   Hyunji Sang2, 5 Author Orcid Image ;   Dong Keon Yon2, 3, 4, 6 Author Orcid Image ;   Sang Youl Rhee2, 5 Author Orcid Image
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  1. Afrisham R, Jadidi Y, Moradi N, Ayyoubzadeh S, Fadaei R, Kiani Ghalesardi O, Farrokhi V, Alizadeh S. Circulating CCN6/WISP3 in type 2 diabetes mellitus patients and its correlation with insulin resistance and inflammation: statistical and machine learning analyses. BMC Medical Informatics and Decision Making 2025;25(1) View
  2. Jin X, Wang Y, Wang J, Gao Q, Huang Y, Shao L, Zhao J, Li J, Li L, Zhang Z, Li S, Liu Y. A Machine Learning Approach to Differentiate Cold and Hot Syndrome in Viral Pneumonia Integrating Traditional Chinese Medicine and Modern Medicine: Machine Learning Model Development and Validation. JMIR Medical Informatics 2025;13:e64725 View
  3. Zhang M, Liu Q, Zhan J, Gao J, Xie D, Liu J. A dual attention and multi-scale fusion network for diabetic retinopathy image analysis. Frontiers in Medicine 2025;12 View