Yariv Colbeci
Papers
1
Total Citations
2
H-Index
1
About
Yariv Colbeci is a researcher focused on advancing surgical workflow analysis through computational methods. His work centers on applying video analysis techniques to improve the efficiency and predictability of operating room procedures. His most notable contribution, "Estimated Time to Surgical Procedure Completion: An Exploration of Video Analysis Methods" (2023), investigates how machine learning and computer vision can be leveraged to estimate remaining surgical time from live video feeds. This research addresses a critical challenge in perioperative logistics—reducing delays and optimizing resource allocation. While his citation count is still growing, with 2 citations to date, this early work demonstrates a promising approach to integrating artificial intelligence into clinical decision-making. Colbeci’s research sits at the intersection of computer science and healthcare, offering practical tools for surgical teams to better manage scheduling and patient flow. His work is particularly relevant for researchers and students interested in medical AI, video-based analytics, and the operational optimization of healthcare systems.
Research Focus
Key Achievements
Top Papers
- 1