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, ...

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

Artificial Intelligence (AI) and Machine Learning (ML) are becoming core technologies across industries. Organizations are using these technologies to improve ...

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

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

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 ...

Sticking to an exercise routine is a challenge many people face. But a research team is using machine learning to uncover what keeps individuals committed to their workouts. Sticking to an exercise ...