Prediction of mortality following pediatric heart transplant using machine learning algorithms.
Journal:
Pediatric transplantation
Published Date:
May 1, 2019
Abstract
BACKGROUND: Optimizing transplant candidates' priority for donor organs depends on the accurate assessment of post-transplant outcomes. Due to the complexity of transplantation and the wide range of possible serious complications, recipient outcomes are difficult to predict accurately using conventional multivariable regression. Therefore, we evaluated the utility of 3 ML algorithms for predicting mortality after pediatric HTx.