The researchers argue that their findings, published in Scientific Reports, could help clinicians anticipate which patients ...

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 ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

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 ...

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 ...

Overview: The Java ecosystem now offers a wide variety of ML frameworks - from lightweight toolkits for data mining to ...