Sarah Choksi
Papers
8
Total Citations
68
H-Index
5
About
Sarah Choksi is pioneering the integration of artificial intelligence and computer vision into robotic-assisted surgery, with a focus on real-time surgical phase recognition and automated skill assessment. Her most impactful work, "Bringing Artificial Intelligence to the operating room: edge computing for real-time surgical phase recognition" (21 citations), demonstrates how AI can be deployed directly in surgical settings to analyze video feeds and identify procedural steps as they happen. Choksi has built on this foundation with studies on surgical phase recognition in inguinal hernia repair (20 citations) and kinematic data profiling for robotic procedures, using deep learning models to break down technical performance and predict outcomes. Her research extends to 3D tooltip tracking from monocular video, automatic suturing assessment in dry-lab simulations, and standardizing surgical training with objective performance indicators. With over 68 cumulative citations across her key papers, Choksi’s work is shaping the future of surgical education and quality assurance, offering tools that can provide real-time feedback, enhance patient safety, and reduce complications. Her contributions are particularly notable for their translational potential, bridging cutting-edge AI with practical operating room applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7
- 8