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Explainable machine learning integrating biochemical and metabolomic biomarkers with conventional clinical factors improves chronic kidney disease prediction and risk stratification | Synapse
March 3, 2026
Open Access
Explainable machine learning integrating biochemical and metabolomic biomarkers with conventional clinical factors improves chronic kidney disease prediction and risk stratification
JM
Jing Ma
RL
Ruiyan Liu
XF
Xin Feng
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Puntos clave
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.
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Ma et al. (Thu,) studied this question.
synapsesocial.com/papers/69a75dcbc6e9836116a28083
https://doi.org/https://doi.org/10.1186/s12882-026-04781-9