AI-driven decision support aims to utilize more donor hearts for transplant
Reports and Proceedings
Updates every hour. Last Updated: 8-Jun-2026 03:16 ET (8-Jun-2026 07:16 GMT/UTC)
A routine heart scan might soon do more than just check for clogged arteries; it could act as a crystal ball for your cardiac health. Researchers at Kumamoto University have revealed that by combining two specific markers from a standard cardiac Computed Tomography (CT) scan, they can identify patients at the highest risk for future heart failure and death.
In a National Institutes of Health (NIH)-funded study, researchers developed a cancer assessment tool that can identify high-risk patients and the tumor cells linked to that risk. The model, called scSurvival, uses a machine learning framework designed to analyze large-scale data at single-cell resolution.
Oregon Health & Science University researchers have developed a first-of-its-kind method to predict cancer patient survival using advanced molecular data from individual cells.
Survival analysis is central to clinical oncology. Modern cancer studies can now measure gene activity in single cells from a patient’s tumor and link this information to how long patients live. However, until now, there has not been a good way to use this detailed cell-level data to directly predict survival.