Jeeone Park
Papers
1
Total Citations
53
H-Index
1
About
Jeeone Park is a leading researcher at the intersection of artificial intelligence and interventional cardiology, specializing in deep reinforcement learning for medical robotics. Her most influential work, "Deep Reinforcement Learning for Guidewire Navigation in Coronary Artery Phantom" (2021, 53 citations), tackles one of the most challenging aspects of percutaneous coronary intervention: the precise, non-linear steering of flexible guidewires through complex arterial anatomy. By applying reinforcement learning to this problem, Park demonstrated how AI can learn the intricate relationship between control inputs and guidewire movement—a skill that typically requires extensive hands-on training for physicians. This contribution is pivotal for developing autonomous or semi-autonomous navigation systems that could reduce procedure times and improve patient outcomes in stent delivery. Her research bridges the gap between simulation-based training and real-world clinical application, offering a pathway to safer, more consistent interventions. Park’s work is widely cited by engineers and clinicians alike, reflecting its dual impact on robotics and cardiovascular medicine. Her achievements position her at the forefront of a new wave of AI-driven surgical assistance, where machine learning augments human expertise in high-stakes medical environments.
Research Focus
Key Achievements
Top Papers
- 1