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, ...

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

Adults with congenital heart disease (CHD) have a persistently high risk for cardiac reoperation, according to a new study.

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

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 ...

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

Internal iliac and obturator lymph nodes are common sites of metastasis in rectal cancer. This study developed a machine learning (ML) model using clinical data to predict lymph node metastasis and ...

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 ...

Recent study reveals machine learning's potential in predicting the strength of carbonated recycled concrete, paving the way ...

Among patients with chronic noncancer pain, a novel machine learning model effectively predicts opioid use disorder risk.