Article

Personalized Decision Making for Coronary Artery Disease Treatment using Offline Reinforcement Learning

2024-10-15

Abstract excerpt

<title>Abstract</title> <p>Choosing optimal revascularization strategies for patients with obstructive coronary artery disease (CAD) remains a clinical challenge. While randomized controlled trials offer population-level insights, gaps remain regarding personalized decision-making for individual patients. We applied off-policy reinforcement learning (RL) to a composite data model from 41,328 unique patients with...

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Literature Corpus work: ad2b5ced-6240-50c4-8be2-881d08697b2f
DOI: 10.21203/rs.3.rs-4911576/v1

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