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 ...

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

Patients at primary care clinics received more dementia diagnoses after implementation of a machine-learning tool designed to ...

Self-organizing maps, and the machine learning protocol involved in creating them, have been in use since the 1980s, Lawrence ...

A new algorithmic framework that can predict flooding could help save lives and reduce the devastation as climate change drives more intense and unpredictable rainfall.

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic ...

Social determinants of health and disease complexity were both key factors influencing gaps in care for congenital heart ...

The UCLA Biomedical Artificial Intelligence Research Lab is using machine learning to improve the lives of patients. Machine learning is a field of AI that learns from existing data to make ...

Reduced coronary blood flow, measured with an artificial intelligence-based imaging tool, predicted future cardiovascular ...