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AI Tool ONCO-ACS Predicts Heart Attack Risks in Cancer Patients

EurekAlertResearch
AI Tool ONCO-ACS Predicts Heart Attack Risks in Cancer Patients

University of Leicester researchers have developed ONCO-ACS, an AI-powered model to predict mortality, bleeding, and ischaemic events in cancer patients after heart attacks.

Key Details

  • 1ONCO-ACS is an AI model combining cancer-related and standard clinical data to predict death, bleeding, or cardiovascular events within six months post-heart attack.
  • 2The study analyzed data from over 1 million heart attack patients, including more than 47,000 with cancer, from England, Sweden, and Switzerland.
  • 3Results showed nearly one in three cancer patients died within six months, one in 14 suffered major bleeding, and one in six had another cardiovascular event.
  • 4The model is published in The Lancet and funded by Cancer Research UK and the British Heart Foundation.
  • 5The tool aims to guide personalized treatment decisions and design future trials for this complex patient group.

Why It Matters

This model addresses a significant clinical gap by offering tailored risk assessment for cancer patients post-heart attack, a group with limited guidance so far. Its real-world data approach and integration potential could improve patient outcomes and inform more precise treatment strategies.

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