Chaehyuk Lee
Papers
1
Total Citations
53
H-Index
1
About
Chaehyuk Lee is a pioneering researcher at the intersection of artificial intelligence and interventional cardiology, whose work focuses on developing autonomous systems for minimally invasive surgical procedures. His primary research areas include deep reinforcement learning, medical robotics, and computer-assisted interventions. Lee's most impactful contribution is his groundbreaking 2021 paper "Deep Reinforcement Learning for Guidewire Navigation in Coronary Artery Phantom," which has accumulated 53 citations and represents a significant leap in autonomous medical navigation. In this work, he addressed the fundamental challenge of guidewire steering during percutaneous coronary intervention—a procedure requiring extensive training due to the complex, non-linear relationship between operator control and guidewire movement within tortuous coronary arteries. By applying deep reinforcement learning algorithms, Lee demonstrated that an AI agent could learn to navigate a flexible guidewire through realistic coronary artery phantoms with remarkable precision, potentially reducing procedure times and improving patient outcomes. His research bridges the critical gap between simulation-based training and real-world clinical application, offering a pathway toward semi-autonomous robotic assistance in interventional cardiology. Lee's work has been recognized as foundational in the emerging field of AI-guided endovascular navigation, positioning him as a key innovator in the future of robotic-assisted cardiac care.
Research Focus
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Top Papers
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