xIt would be greatly beneficial to physicians trying to save lives in intensive care units if they could be alerted when a patient’s condition rapidly deteriorates or shows vitals in highly abnormal ...

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, ...

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 ...

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 ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...