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

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.

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

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 ...

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

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 ...

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