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.

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 ...

Assessment of Circulating Tumor DNA Burden in Patients With Metastatic Gastric Cancer Using Real-World Data Endometrial cancer (EC) is the most common gynecologic cancer in the United States with ...

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

Feasibility and Implementation of a Digital Health Intervention Electronic Patient-Reported Outcomes–Based Platform for Telemonitoring Patients With Breast Cancer Undergoing Chemotherapy Among the 76 ...

Impulse AI is building an autonomous machine learning engineer that turns data into production models from a simple prompt. Founded in 2025 and based in California, the company enables teams to build, ...

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

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

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