Johns Hopkins University and Stanford University researchers have unveiled a method for training robots to mimic human doctors’ surgical techniques.
On Monday, SiliconANGLE reported that the research team integrated a sophisticated machine-learning model to analyze surgical procedures captured by cameras mounted on the robot into the existing Da Vinci robotic surgery system. The Da Vinci robotic surgery system comprises three key components: the robotic cart, the operating console, and the endoscopic stack.
The model incorporates a feedback mechanism that enables the robot to autonomously assess and enhance its performance. The research team explained that this feature allows the robot to achieve surgical precision and agility comparable to that of a human surgeon without constant supervision.
The team trained the robot to master the exact movements required to perform tasks such as needle manipulation, tissue handling, and suturing. Furthermore, they equipped the robot to adapt to diverse surgical styles and environments, which improved the system’s adaptability by allowing it to deal with subtle differences and unpredictability in real-world surgical procedures.
Dr. Axel Krieger, an associate professor at Johns Hopkins Whiting School of Engineering who led the research, emphasized that their goal is not to replace surgeons but to simplify surgical procedures.
Most Commented