Colorectal Surgical Intelligence
Shih-Feng (Fredric) Huang, MD
A unified framework linking preoperative planning, intraoperative proficiency, and postoperative outcomes in robotic colorectal surgery.
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Attending Colorectal Surgeon at Kaohsiung Veterans General Hospital. Concurrently a PhD student in Computer Science (Medical Informatics track) at National Cheng Kung University.
Research lives at the intersection of minimally invasive colorectal surgery, machine learning, and surgical video analysis. The goal: turn the implicit judgments of an experienced surgeon into measurable, reproducible quantities.
Selected recent work
- A scalable, annotation-free pipeline for automated CT pelvimetry: a validation study with landmark uncertainty analysis and clinical correlation.
- A fully automated CT-based pelvimetry pipeline for quantifying mid-pelvic surgical workspace in rectal cancer.
- Technical proficiency assessment of robotic intracorporeal single-stapling colorectal anastomosis using video-based RA-CUSUM.
15 peer-reviewed articles since 2021 — first author on 12. See Research for the full framework, or Publications for the complete list.