The Utility of Machine Learning for Predicting Donor Discard in Abdominal Transplantation.

The XGBoost method demonstrated a significant improvement in predicting donor allograft discard for both kidney and livers in solid organ transplantation procedures. Machine learning methods are well suited to be incorporated into the clinical workflow; they can provide robust quantitative predictions and meaningful data insights for clinician consideration and transplantation decision-making. This article is protected by copyright. All rights reserved.