A large study applies advanced machine learning to identify shared risk factors and predictors of disease onset in patients with epilepsy and depression.

Researchers used a process called symbolic regression to derive the equations from a biogeochemical model of the ocean.

The seven companies listed here cover the realistic range of what a buyer will encounter in 2026: embedded ML teams that own ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...

However, by the late 1970s, there was disappointment that the two main approaches to computing in medicine — rule-based systems and matching, or pattern recognition, systems — had not been as ...

With peak wildfire season underway in California, PG & E's Chief Meteorologist Scott Stenfel held a virtual Wildfire Season ...

UTokyo and Kubota develop a drone potato yield prediction method combining multispectral imagery, AI, and growth models.

MIT researchers created a technique that captures chemical arrangements across materials to improve predictions of how metal ...