The promise and reality of machine-learning models in kidney transplantation.

Abstract

There have been numerous advances in statistical methods and computing technologies over the past decades, including the use of machine-learning models. In the current study, Truchot et al. rigorously evaluated the performance of different machine-learning models compared with traditional Cox proportional hazard models. Results of the study indicated that a Cox model had equivalent or superior performance than machine-learning models and can be relied on for predicting graft survival in kidney transplantation.