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About this paper
Parham M. Kebria, Saeid Nahavandi, Mehrdad Saif, Fernando Bello
SurGPT analyzes robotic-surgery training video to identify the exercise, estimate skill, and describe surgical motion in text. It uses a convolutional image encoder and temporal transformer, with separate prediction outputs and uncertainty-weighted task losses. On reported test data for knot tying, needle passing, and suturing, it achieves 100.0% task and 91.7% skill-classification accuracy; generalization and clinical usefulness remain unestablished.
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