Min Seo Choi

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About

Min Seo Choi is a pioneering researcher in the intersection of anesthesiology and artificial intelligence, with a primary focus on perioperative hemodynamic monitoring and surgical safety. Her most notable contribution is the development of a deep learning model to predict blood pressure changes during robotic laparoscopic low abdominal surgery, specifically addressing the complex interplay between abdominal pressure variations and patient positioning. This work, published in 2022 and garnering 4 citations, represents a critical advance in intraoperative hypertension management, a major cause of negative surgical outcomes. By leveraging machine learning to anticipate hemodynamic instability during CO₂ insufflation and steep Trendelenburg positioning, Choi has opened new pathways for real-time, data-driven clinical decision support. Her research directly addresses a pressing challenge in modern robotic surgery, where traditional monitoring often fails to predict sudden BP fluctuations. Though early in her citation trajectory, Choi’s work is foundational for the emerging field of AI-assisted anesthesia, offering a blueprint for safer, more personalized perioperative care. Her innovative approach positions her as a key figure in the convergence of computational methods and clinical anesthesiology.