Papers
2
Total Citations
31
H-Index
1
About
Dr. Hee-Soo Kim is a leading anesthesiology researcher whose work focuses on perioperative pulmonary care and the application of machine learning to improve patient outcomes. Her key contributions center on preventing postoperative pulmonary complications (PPCs), a major source of morbidity after surgery. In a landmark 2023 randomized controlled trial, Dr. Kim demonstrated that a driving pressure-guided positive end-expiratory pressure (PEEP) strategy significantly reduces PPCs in patients undergoing laparoscopic or robotic surgery, a finding with immediate clinical impact (30 citations). She is also at the forefront of integrating artificial intelligence into perioperative medicine. Her pioneering work on a machine learning model that uses real-time spirometry signal data to predict immediate postoperative desaturation represents a critical advance. By enabling the early identification of patients at risk for this common and dangerous complication, her research paves the way for proactive, preventive interventions. Dr. Kim’s work uniquely bridges rigorous clinical trial methodology with cutting-edge data science, establishing her as a key figure in the evolution of precision anesthesia and safer surgical care.
Research Focus
Key Achievements
Top Papers
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