Sung Hwan Cho

Papers

Total Citations

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About

Sung Hwan Cho is a pioneering researcher in anesthesiology and perioperative medicine, with a core focus on leveraging artificial intelligence to enhance patient safety during robotic and laparoscopic surgeries. His 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 clinical challenge: the dangerous blood pressure fluctuations caused by CO₂ insufflation and steep Trendelenburg positioning. By developing a deep learning model that predicts intraoperative hypertension from abdominal pressure changes, Cho has introduced a novel, data-driven approach to preempt hemodynamic instability—a contribution that has already garnered 4 citations and growing recognition. This work bridges the gap between real-time surgical physiology and predictive analytics, offering anesthesiologists a tool to anticipate and mitigate adverse events before they occur. Cho’s research stands at the intersection of machine learning and clinical anesthesiology, demonstrating how AI can transform routine monitoring into proactive care. His achievements highlight a commitment to reducing perioperative risks, making him a notable figure in the emerging field of AI-assisted anesthesia management.