Young-Seob Jeong
Papers
1
Total Citations
4
H-Index
1
About
Young-Seob Jeong is a researcher at the forefront of applying deep learning to anesthesiology and perioperative medicine. His work centers on developing predictive models that enhance patient safety during surgery, with a particular focus on the complex physiological changes induced by robotic laparoscopic procedures. Jeong’s most notable contribution is his pioneering study on predicting blood pressure fluctuations during robotic low abdominal surgery, where he leveraged deep learning to forecast how abdominal pressure changes—from CO₂ insufflation and steep Trendelenburg positioning—affect intraoperative hypertension. This work, published in 2022 with 4 citations, addresses a critical gap in real-time hemodynamic monitoring, offering a data-driven approach to anticipate and mitigate negative patient outcomes. By integrating artificial intelligence with clinical decision-making, Jeong is helping to usher in a new era of precision anesthesia, where subtle physiological shifts can be predicted before they become dangerous. His research stands as a vital step toward safer, more responsive surgical care, demonstrating the transformative potential of machine learning in the operating room.
Research Focus
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Top Papers
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