Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has long been slow, expensive, and heavily empirical. Machine learning is now ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could ...

Opinion: A patent case involving inventor Guillaume Desjardins has evolved into a cornerstone of modern patent eligibility ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

The team utilized machine learning to analyze public data from the National Health and Nutrition Examination Survey.

Around the world, millions of families have suffered forcible separation, through war, trafficking, natural disasters, or ...

Researchers at University of Jyväskylä (Finland) advance understanding of gold nanocluster behavior at elevated temperatures ...

Lawrence Berkeley National Laboratory (Berkeley Lab) is working to transform petabytes of imaging data from advanced light ...

Interview Kickstart today announced the launch of its Advanced Machine Learning Program, a specialized interview preparation track designed for engineers and data professionals preparing for machine ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

A novel machine learning version of the Opioid Risk Tool provides high precision screening for opioid use disorder in chronic pain patients.

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...