Juseong Jin
Papers
1
Total Citations
1
H-Index
1
About
Juseong Jin is a researcher at the forefront of perioperative medicine and biomedical data science, with a primary focus on predicting and preventing postoperative pulmonary complications. His most cited work introduces a novel machine learning model that leverages real-time spirometry signal data to forecast immediate postoperative desaturation—a common and dangerous complication following surgery. By demonstrating that dynamic changes in respiratory mechanics can serve as early warning indicators, Jin’s research bridges a critical gap in clinical decision support. Though early in his career, with his top-cited paper accumulating 1 citation, his work is gaining traction for its practical potential to reduce patient risk and improve recovery outcomes. Jin’s contributions underscore a commitment to translating physiological signals into actionable, real-time predictions, positioning him as an emerging voice in the integration of artificial intelligence with anesthesiology and critical care. His research holds promise for shaping future preventive protocols in surgical settings.
Research Focus
Key Achievements
Top Papers
- 1