Clinical decision system for chronic kidney disease staging using machine learning

The findings demonstrate the effectiveness of CatBoost and GAN AML in accurately classifying CKD stages, highlighting the importance of expert knowledge in selecting feature selection strategies to enhance ML model performance. Future research directions include validating diverse datasets, integrating with clinical practice, and improving interpretability and explainability in CKD prediction models.