Daniel P. Bitner
Northwell Health, University of Virginia, Lenox Hill Hospital
Papers
10
Total Citations
155
H-Index
7
About
Daniel P. Bitner is a leading researcher at the intersection of robotic surgery, artificial intelligence, and surgical education. His work focuses on objective skill assessment, surgical phase recognition, and the integration of AI into the operating room. Bitner’s major contributions include pioneering the use of computer vision and deep learning for automated quality assessment in robotic-assisted surgeries, particularly for inguinal hernia repair and cholecystectomy. His studies on kinematic data and surgical performance have advanced understanding of the learning curve and technical skill heterogeneity among surgeons. With over 150 citations across his most-cited papers, Bitner’s research has demonstrated that blinded intraoperative evaluations can mitigate gender bias, and his work on edge computing for real-time surgical phase recognition brings AI directly into clinical workflows. Notable achievements include his leadership in the SAGES AI task force and his role in developing video acquisition frameworks for surgical research. Bitner’s work is shaping the future of data-driven, equitable, and efficient surgical practice.
Research Focus
Key Achievements
Top Papers
- 1
- 2Does Robotic Surgical Simulator Performance Correlate With Surgical Skill?31 citations · 2017
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- 6Blinded intraoperative skill evaluations avoid gender-based bias10 citations · 2022
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- 9Outcome prediction in bariatric surgery through video-based assessment4 citations · 2022
- 10