A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.

Facing strict privacy laws, telcos use AI-generated synthetic data as a compliant workaround to train ML models without exposing sensitive customer information.

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...

People's decisions are known to be influenced by past experiences, including the outcomes of earlier choices. For over a century, psychologists have been trying to shed light on the processes ...

Drug discovery is like molecular Tetris. Chemists snap atoms together, adjusting the pieces until everything fits, and suddenly, a molecule makes a promising new medicine. Normally, creating better ...

Machine-learning models accurately pinpointed differences in immune responses in healthy controls and those living with HIV.

A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a ...

Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...

Researchers at Fondazione Policlinico Universitario Agostino Gemelli IRCCS have developed a promising machine learning algorithm capable of predicting survival and cause of death for patients with ...

Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...

In one case, an AI checker pre-installed on a school-issued Chromebook flagged a student's essay on Harrison Bergeron by Kurt Vonnegut as "18% AI-written" simply because ...