Explainable machine learning integrating biochemical and metabolomic biomarkers with conventional clinical factors improves chronic kidney disease prediction and risk stratification

Key Points

• Enhanced prediction of chronic kidney disease risk using machine learning with biomarkers.
• The model incorporates biochemical and metabolomic biomarkers alongside clinical factors.
• Analysis shows significant improvement in risk stratification metrics for chronic kidney disease.
• These findings support the need for more precise identification of at-risk individuals.