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

Source
EurekAlert
Related News

AI Accelerates Radiopharmaceuticals, Boosts Personalized Dosimetry in Cancer
Machine learning is driving advancements in radiopharmaceutical drug discovery and optimizing patient-specific dosimetry for precision cancer therapy.

Physicians Overly Trust Erroneous AI, Ignore Contradictory Evidence
Physicians tend to trust incorrect AI advice, even when evidence contradicts it, suggesting risks in clinical decision-making with AI tools.

Concerns Raised Over Unverified Datasets in AI Health Prediction Models
A new study finds widely used AI health prediction models are built on datasets with unverifiable origins, raising safety and validity concerns.