Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

The field of additive manufacturing is undergoing a profound transformation as artificial intelligence (AI) and machine learning (ML) become integral to the ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

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 ...

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

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

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

Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New ...