Accessibility settings

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/58107, first published .
Man checks blood sugar with a glucose meter, a diabetes management tool.

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

Journals

  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
  4. Lee H, Hwang J, Yon D, Rhee S. Multimodal and Multidimensional Artificial Intelligence Technology in Obesity. Journal of Obesity & Metabolic Syndrome 2025;34(4):394 View
  5. Dou Y, Liu J. Interpretable machine learning algorithms for diagnostic prediction of diabetic retinopathy. Technology and Health Care 2026;34(2):124 View
  6. Mata-Lima A, Serrano-Olmedo J, Paquete A. Leveraging ICT Tools to Improve Kidney Health: A Comprehensive Review of Innovations in Nephrology. Healthcare 2026;14(6):785 View
  7. Kim T, Kim S, Kim Y, Lee H, Hwang S, Yang S, Smith L, Hajek A, Woo S, Yon D. Machine Learning Prediction Model for Dyslipidemia and Its Association With Atherothrombotic Events in 3 Independent Cohorts From South Korea, Japan, and the United Kingdom: Algorithm Development and Validation Study. JMIR Medical Informatics 2026;14:e81130 View