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 ...

Cutting-edge machine learning tools reveal hidden patterns in Alzheimer’s disease mouse behavior, opening the door to innovative treatments targeting neuroinflammation. Study: Machine learning reveals ...

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...

New machine learning study reveals how early-life chronic conditions like arthritis, mood disorders, and hypertension may drive premature death in people with IBD—highlighting critical opportunities ...

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...

Scientists used a new video-based machine learning tool to pinpoint otherwise-undetectable signs of early disease in mice that were engineered to mimic key aspects of Alzheimer's. Their work sheds ...

Plasma mirrors capable of withstanding the intensity of powerful lasers are being designed through an emerging machine learning framework. Researchers in Physics and Computer Science at the University ...