A gradient boosting machine model performed best among five machine learning models tested for predicting delirium, according to findings recently published in JAMA Network Open. “Existing ...

Extreme Gradient Boosting (XGBoost) provided the best performance in each paper in which it was tested. Numerous heterogeneities exist, including definition of “injury”, granularity of data and scope ...

A key objective of behavioral science research is to better understand how people make decisions in situations where outcomes are unknown or uncertain, which entail a certain degree of risk.

The BO-GBRT model accurately predicts compressive strength in self-compacting concrete with recycled aggregates, improving upon traditional testing methods.