Understanding how ozone behaves indoors is vital for assessing human health risks, as people spend most of their time inside.

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using comprehensive health examination data from nearly 37 701 individuals.Methods ...

A machine learning random forest regression system predicts a single numeric value. A random forest is an ensemble (collection) of simple decision tree regressors that have been trained on different ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

A: A random forest is a machine-learning method that makes predictions by combining the decisions of many simpler models called decision trees. A decision tree works like a tree from bottom-up. At ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression technique (and a variant called bagging regression), where the goal is to ...