Yang Hoon Chung

About

Yang Hoon Chung is a researcher at the forefront of applying artificial intelligence to anesthesiology and perioperative medicine. Their primary research focuses on the development of deep learning models to predict and manage hemodynamic changes during complex surgical procedures, particularly robotic laparoscopic surgery. Chung’s most cited work, a 2022 study on predicting blood pressure fluctuations during robotic lower abdominal surgery, demonstrates a novel approach to a critical clinical challenge: using machine learning to forecast hypertensive events triggered by pneumoperitoneum and the Trendelenburg position. This contribution, which has garnered early citations, addresses a significant gap in intraoperative patient safety by enabling proactive rather than reactive blood pressure management. By leveraging deep learning to analyze the interplay between abdominal pressure changes and cardiovascular responses, Chung’s research offers a pathway toward more precise, data-driven anesthesia care. Their work stands as a promising step in integrating artificial intelligence into the operating room, with the potential to reduce perioperative complications and improve outcomes for patients undergoing minimally invasive robotic procedures.

Research Focus

Key Achievements

Top Papers

1. 1
   Prediction of blood pressure changes associated with abdominal pressure changes during robotic laparoscopic low abdominal surgery using deep learning

   4 citations · 2022

Key Collaborators

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