1 citations · 2 across the 4 of their papers we have counts for
4 papers
A Multi-Agent LLM Framework for Rating the Quality of Surgical Feedback
Rafal Kocielnik, J. Everett Knudsen, Steven Y. Cen +7
Verbal feedback delivered by attending surgeons in the operating room plays a critical formative role in resident trainee skill acquisition. Yet, assessing the quality of trainer f…
Generating Natural-Language Surgical Feedback: From Structured Representation to Domain-Grounded Evaluation
Firdavs Nasriddinov, Rafal Kocielnik, Anima Anandkumar +1
High-quality intraoperative feedback from a surgical trainer is pivotal for improving trainee performance and long-term skill acquisition. Automating natural, trainer-style feedbac…
Automating Feedback Analysis in Surgical Training: Detection, Categorization, and Assessment
Firdavs Nasriddinov, Rafal Kocielnik, Arushi Gupta +4
This work introduces the first framework for reconstructing surgical dialogue from unstructured real-world recordings, which is crucial for characterizing teaching tasks. In surgic…
Multi-Modal Self-Supervised Learning for Surgical Feedback Effectiveness Assessment
Arushi Gupta, Rafal Kocielnik, Jiayun Wang +5
During surgical training, real-time feedback from trainers to trainees is important for preventing errors and enhancing long-term skill acquisition. Accurately predicting the effec…