The promise and reality of machine-learning models in kidney transplantation
1Department of Surgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA; Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA.
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.
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