Misoon Lee

Papers

Total Citations

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About

Misoon Lee is a researcher at the forefront of applying artificial intelligence to perioperative medicine, with a primary focus on hemodynamic monitoring and surgical safety. Her most cited work, "Prediction of blood pressure changes associated with abdominal pressure changes during robotic laparoscopic low abdominal surgery using deep learning" (2022), addresses a critical challenge in robotic surgery: the dangerous blood pressure fluctuations caused by CO₂ insufflation and steep Trendelenburg positioning. By developing a deep learning model that predicts intraoperative hypertension, Lee’s research directly targets the prevention of negative patient outcomes linked to hemodynamic instability. Though her citation count is still growing (4 citations for this key paper), her work represents a novel intersection of anesthesiology, robotics, and machine learning—a field with immense potential for improving surgical precision and patient safety. Lee’s contributions are particularly notable for their practical clinical application, offering a data-driven approach to anticipate and mitigate risks during complex minimally invasive procedures. Her research is essential reading for anesthesiologists, surgical teams, and AI engineers seeking to integrate predictive analytics into real-time operating room decision-making.