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, ...

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

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

Enhanced prediction capability: Machine learning-based system matches and in some cases outperforms traditional forecasting systems, with particular improvements in northern Europe where conventional ...

An agentic AI tool for battery researchers harnesses data from previous battery designs to predict the cycle life of new ...

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 ...

Data is fundamental to hydrological modeling and water resource management; however, it remains a major challenge in many ...