Artificial Intelligence In Robot-Assisted Surgery Applications On Surgical Skills Assessment And Transfer

Safety and high-quality education are very important in the learning procedure of surgical trainees before operation on real patients. In the conventional method of education and evaluation, residents are educated and evaluated through traditional methods that are cumbersome, qualitative, and subjective. Quantitative surgical skills assessment and transfer approaches can improve the quality and accuracy of the evaluation and education in surgical training programs. In this chapter, we propose a comprehensive review of AI-powered approaches that detect and incorporate the underlying skills-related features of surgical trajectories to classify and improve the levels of expertise of users in surgical training platforms. To this end, we investigate the functionality, advantages, and drawbacks of current skills evaluation and transfer methods with a focus on robot-assisted surgery applications.