AssetID: 54917499
Headline: RAW VIDEO: Surgical Robot Performs First Ever Autonomous Gall Bladder Surgery
Caption: A surgical robot trained using videos of real procedures has successfully completed a key phase of a gallbladder removal on a lifelike model—without any human assistance. The robot, developed by researchers at Johns Hopkins University in the United States, responded to verbal instructions during the operation, learning and adapting much like a junior surgeon guided by a more experienced colleague. The robot demonstrated the poise and precision of a seasoned human surgeon, even when faced with the sorts of complications often encountered in real-life emergencies. “This advancement moves us from robots that can execute specific surgical tasks to robots that truly understand surgical procedures,” said Axel Krieger, a medical roboticist at Johns Hopkins. The achievement marks a major step forward for autonomous surgical systems. While previous surgical robots followed rigid pre-programmed paths, this new model combines mechanical precision with the adaptability and decision-making typically seen in humans. "This is a critical distinction that brings us significantly closer to clinically viable autonomous surgical systems that can work in the messy, unpredictable reality of actual patient care," Krieger added. The system, known as the Surgical Robot Transformer–Hierarchical (SRT-H), is built on the same machine learning architecture that powers AI tools such as ChatGPT. It can interact using natural language, responding to spoken instructions such as “grab the gallbladder head” or corrections like “move the left arm a bit to the left.” It learns from each exchange. In contrast to earlier systems, which required specially marked tissues and tightly controlled environments, SRT-H can adjust to different anatomical features in real time, make independent decisions mid-operation, and correct its own mistakes. Krieger likened his earlier robot, the Smart Tissue Autonomous Robot (STAR), which in 2022 performed the first autonomous laparoscopic surgery on a live pig, to "teaching a robot to drive along a carefully mapped route." The new system, he said, is "like teaching a robot to navigate any road, in any condition, responding intelligently to whatever it encounters." Lead author Ji Woong "Brian" Kim, formerly at Johns Hopkins and now at Stanford University, called the project a significant breakthrough. “This work represents a major leap from prior efforts because it tackles some of the fundamental barriers to deploying autonomous surgical robots in the real world,” he said. “Our work shows that AI models can be made reliable enough for surgical autonomy—something that once felt far-off but is now demonstrably viable.” The team previously trained the robot to complete three basic tasks—needle manipulation, tissue lifting, and suturing—each lasting only seconds. The gallbladder removal, however, required the completion of 17 distinct steps, including identifying ducts and arteries, placing surgical clips, and cutting tissue. To prepare, the robot was shown videos of Johns Hopkins surgeons performing the procedure on pig cadavers. Each video was paired with captions explaining the steps. After training, the robot completed the surgery with 100% accuracy. Although it took more time than a human surgeon, the outcome was on par with expert performance. “Just as surgical residents often master different parts of an operation at different rates, this work illustrates the promise of developing autonomous robotic systems in a similarly modular and progressive manner,” said Dr Jeff Jopling, a surgeon at Johns Hopkins and co-author on the study. The robot also handled unexpected scenarios well. It successfully operated across a variety of anatomical conditions and adapted when the researchers altered its starting position or used dye to simulate bleeding. “To me it really shows that it’s possible to perform complex surgical procedures autonomously,” said Krieger. “This is a proof of concept that it’s possible, and this imitation learning framework can automate such complex procedures with such a high degree of robustness.” The team now plans to expand the robot's capabilities, with the aim of performing a fully autonomous surgery in future trials.
Keywords: robot, science, technology, tech, medicine, feature, photo, video
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