Researchers from Stanford University and Johns Hopkins University have developed a novel method for teaching surgical robots, showing that by merely watching human surgeons, these devices may be trained to carry out particular duties. Bypassing the conventional, time-consuming programming process, this novel technique known as imitation learning allows robots to acquire human-level surgical abilities through the observation of doctors performing procedures on video.
To test their theory, the scientists employed the da Vinci Surgical System, a popular robotic platform for minimally invasive procedures. The researchers fed the robot hundreds of hours of video from wrist-mounted cameras that recorded the complex movements of human surgeons carrying out three essential tasks needle manipulation, tissue lifting, and suturing instead of manually programming each operation. The robot replicated the exact methods the surgeons displayed by absorbing this kinematic data, which converts physical movement into mathematical instructions.
In this instance, the robot learnt from visual data instead of text, but the learning process is similar to how AI models like ChatGPT are taught on large datasets. It was quite amazing how well the robot was able to anticipate and mimic moves after viewing the movies; its performance was comparable to that of skilled human surgeons.
The AI’s learning abilities surpassed expectations, according to Axel Krieger, an assistant professor at Johns Hopkins. Even under unexpected circumstances, the robot might be able to adjust on its own, picking up a fallen needle and carrying on without assistance from a human. This creates interesting opportunities for robotic surgery in the future. Although the prospect of surgical robots may seem disconcerting at first, the accuracy of AI-powered devices may lower the possibility of medical mistakes, freeing up human surgeons to concentrate on more intricate and surprising surgical procedures. With the potential to transform the field of medical robotics, this research represents a critical turning point in the development of AI-powered healthcare.