A new AI-powered risk prediction model assists clinicians in treating cancer patients following a heart attack by combining oncology and cardiovascular data.
Key Details
- 1Researchers at University of Zurich developed ONCO-ACS, an AI-based tool for individualized risk assessment in cancer patients post-heart attack.
- 2Used data from over 1 million heart attack patients, including 47,000 with cancer, from England, Sweden, and Switzerland.
- 3Cancer patients showed a nearly 1 in 3 mortality rate within six months after a heart attack.
- 4ONCO-ACS predicts risks of death, major bleeding, or recurrent cardiac event within six months, using both cancer-related and standard cardiovascular data.
- 5The tool is validated and aims to support tailored decisions regarding catheter-based interventions and antiplatelet therapy.
Why It Matters
This is among the first AI tools designed specifically for the intersection of oncology and cardiology, addressing a major gap in risk prediction for a previously overlooked patient population. It could improve outcomes and inform personalized care strategies in radiology and broader clinical management.
Source
EurekAlert
Related News
•EurekAlert
USC Unveils Joint Biomedical Engineering Department Bridging Medicine, Engineering, and Imaging
USC's medical and engineering schools launch a joint biomedical engineering department to accelerate interdisciplinary research and innovation, including imaging and AI.
•EurekAlert
AI Predicts Risks for Outpatient Stem Cell Therapy in Myeloma
Researchers use machine learning to predict adverse events during stem cell therapy for multiple myeloma, improving outpatient safety.
•EurekAlert
AI-Enhanced CT Heart Fat Measurement Boosts Cardiovascular Risk Prediction
AI-derived measurement of heart fat from CT scans significantly improves long-term cardiovascular disease risk prediction.