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

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

Researchers have developed a new "emotionally aware" AI-based model for classifying mental health conditions, which could ...

A machine learning (ML)-based model may aid in-hospital community-acquired pneumonia (CAP) mortality prediction, according to study findings published in Respiratory Medicine. Res ...

RTID system reduces unnecessary temporary diverting ileostomy use in rectal cancer surgery without increasing anastomotic leakage.

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Researchers at the University of California San Diego and the Allen Institute for AI have built a climate emulator that ...

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

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 ...