Surgical Skill

Surgical skill assessment is evolving from subjective evaluations to objective, data-driven methods, aiming to improve surgical training and patient outcomes. Current research heavily utilizes computer vision and machine learning, employing architectures like deep neural networks (including convolutional and recurrent networks), graph neural networks, and Gaussian processes to analyze video and sensor data from both simulated and real surgical procedures. These models analyze instrument movements, hand trajectories, and overall procedural efficiency to predict surgical skill levels, providing real-time feedback and potentially identifying correlations between specific actions and patient outcomes. This shift towards automated, objective assessment promises to revolutionize surgical training and enhance surgical precision.