PitDash: Live Surgery Dashboard
| dc.contributor.author | Keith Lowry | en |
| dc.contributor.author | Brandon Hoang | en |
| dc.contributor.author | Hansa Pradhan | en |
| dc.contributor.author | Yash Kulkarni | en |
| dc.contributor.author | Tesha Yeboah | en |
| dc.contributor.author | Asmi Panigrahi | en |
| dc.contributor.author | Revati Bhavsar | en |
| dc.contributor.author | Sudarshan Manavalan | en |
| dc.date.accessioned | 2025-05-14T23:58:55Z | en |
| dc.date.available | 2025-05-14T23:58:55Z | en |
| dc.date.issued | 2025-05-09 | en |
| dc.description | Our product, PITDASH, is a live detection tool designed to transform the way surgeries are analyzed and understood. Surgeons can upload or livestream videos of their procedures, which are automatically broken into individual frames and processed by a machine learning model that detects which surgical instruments are being used and pinpoints their positions throughout the operation. This information is then visualized through interactive graphs and stored in a user-friendly dashboard. The dashboard allows surgeons to review their procedures afterward and helps them identify usage patterns, evaluate efficiency, monitor instrument movement, and gain insights into surgical techniques. This not only supports performance improvement but can also aid in identifying opportunities to reduce errors or improve patient outcomes. For researchers, the tool provides a valuable dataset for studying surgical practices, comparing techniques, and developing new innovations in the field. For surgical trainees, it offers a powerful educational resource, making it easier to observe expert techniques, understand instrument handling, and reflect on their own performance using data-driven feedback. | en |
| dc.identifier.uri | https://hdl.handle.net/10919/132467 | en |
| dc.rights | Attribution-NonCommercial 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc/4.0/ | en |
| dc.title | PitDash: Live Surgery Dashboard | en |
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