Whether estimating the probability that a disease is present or forecasting risk of deterioration,1 readmission,2 or death,3 most contemporary clinical artificial intelligence (AI) systems are ...

New global modeling shows that about 9.3% of the world's land area is highly vulnerable to the risk of dangerous disease ...

Processing data closer to its source (edge computing) combined with AI allows for faster analysis and decision-making in preventative maintenance, as well as enhances data security. The work flows in ...

Medical device manufacturers have spent decades engineering products that save lives. Many are now discovering that their ...

Artificial intelligence and machine learning are reshaping diabetes prevention, diagnosis, and management across the care continuum. Continuous glucose ...

Walk through enough industrial AI deployments and a pattern becomes uncomfortable to ignore. The pilot works. The model ...

The techniques that have served marketers for over fifty years are evolving rapidly, driven by artificial intelligence, increasing market volatility and a fundamental shift in what we expect ...

Self-supervised reinforcement learning is a technique where agents learn useful representations and skills from the environment through self-generated tasks, such as predicting next states or learning ...

1 Department of Mathematics & Statistical Sciences, Jackson State University, Jackson, MS, USA. 2 Department of Public Health, California State University, Fullerton ...

Extracorporeal membrane oxygenation (ECMO) is a critical life-support intervention for patients with severe cardiopulmonary failure. However, its use is associated with a substantially increased risk ...