Published on in Vol 8 (2024)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/48378, first published
.

Journals
- Valencia M, Kim J, Abbas Z, Lee S. Early Detection of Chronic Kidney Disease in Men Using Lifestyle and Demographic Indicators: A Machine Learning Approach for Primary Healthcare Settings. Healthcare 2026;14(3):405 View
- Bhandurge S, Sambrekar K, Malghan R, Rao K. Review on Exploring Machine Learning Classifiers in the Diagnosis of Chronic Kidney Disease. Sci 2026;8(4):68 View
- Edwina Jospiene M , Nimithap S , Dr Subhadip Bag , Dr. S. Elavarasan , Dr. Prolay Ghosh , Sathiyamoorthy M , S.T. Gopukumar . Machine Learning Algorithms for Predicting CKD Progression: A Real-World Hospital Dataset Analysis. KIDNEYS 2026;15(1):43 View
- Bertok T, Pankuchova I, Jane E, Batova Z, Tkac J. Artificial intelligence in diagnostic software: validation, safety, and lifecycle challenges in Europe. Clinica Chimica Acta 2027;592:121209 View
Books/Policy Documents
Conference Proceedings
- Bhuria R. 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit). Advanced Machine Learning Techniques for Chronic Kidney Disease Prediction and Management View
- Dipto S, Bhoyan F, Ratul S, Islam M, Bin Saad S, Chakraborty S. 2024 6th International Conference on Sustainable Technologies for Industry 5.0 (STI). An Improved Interpretable Transformer Based Approach for Identifying Kidney Abnormalities View
