Surgical Automation

Surgical automation aims to improve surgical precision, consistency, and accessibility through robotic systems performing tasks autonomously or with shared control. Current research heavily utilizes reinforcement learning, often incorporating imitation learning from expert demonstrations and leveraging advanced architectures like actor-critic frameworks and transformer networks, to train robots for diverse surgical subtasks such as dissection, suturing, and tissue manipulation. This field is significant because it promises to enhance surgical outcomes, reduce surgeon workload, and expand access to advanced surgical care, driving innovation in both robotics and artificial intelligence.