A machine learning approach to predicting 30-day mortality following paediatric cardiac surgery: findings from the Australia New Zealand Congenital Outcomes Registry for Surgery (ANZCORS).

Our risk prediction model outperformed logistic regression and achieved a level of discrimination comparable to the PRAiS2 and STS-CHSD mortality risk models (both which obtained AUC = 0.86). Non-linear ML methods can be used to construct accurate clinical risk prediction tools.