Development of a robotic surgery assistance system incorporating AI deep learning technology
Apr 02, 2025
A domestic research team, including Yonsei Cancer Hospital, has developed a robotic surgery assistance system incorporating AI deep learning technology.
A joint research team led by Professor Park Hyung-seok of breast surgery at Yonsei Cancer Hospital, Professor Kim Nam-guk of convergence medicine at Asan Medical Center in Seoul, Professor Lee Ji-ah of breast surgery at Eulji University Hospital in Uijeongbu, and Professor Ho Sung-won of Medical Life Research Center at Korea University Ansan Hospital announced on the 2nd that they have developed a surgical assistance system that can utilize AI deep learning technology by incorporating it into a robotic surgical device.
Unlike open surgery, which cuts the surgical site enough to fit a doctor's hand and furniture, robotic surgery is performed using a small robotic arm of 8mm, and patient satisfaction is high in terms of beauty as well as effectiveness.
Because it uses a very small robotic arm, the practitioner needs training in sophisticated techniques. The research team created a surgical robot system equipped with AI deep learning technology for robotic surgery training. The AI model is an algorithm that extracts learning images every second from actual breast cancer robotic surgery images, learns thousands of images, and accurately predicts the skin plate incision boundary for surgery based on this.
Through real-time analysis according to the condition of the surgical patient, the incision boundary is provided very accurately, the surgical stability is increased, and the basis for judgment is presented to the surgeon.
In particular, the incision boundary presented by the AI model is expected to play a major role in reducing the risk of unnecessary tissue loss or complications that may occur during surgery, with results similar to those indicated directly by breast surgeons.
In the future, the research team will continue to learn breast cancer robotic surgery images in the newly developed AI model to increase the degree of completion.
Professor Park Hyung-seok said, `The demand for robotic surgery through minimally invasive surgery will continue to increase because breast cancer surgery sites can also be linked to women's self-esteem.' `We have developed a technology to effectively conduct robotic surgery training for new specialists.' The findings were published in the latest issue of the international journal `breast cancer research.'
A joint research team led by Professor Park Hyung-seok of breast surgery at Yonsei Cancer Hospital, Professor Kim Nam-guk of convergence medicine at Asan Medical Center in Seoul, Professor Lee Ji-ah of breast surgery at Eulji University Hospital in Uijeongbu, and Professor Ho Sung-won of Medical Life Research Center at Korea University Ansan Hospital announced on the 2nd that they have developed a surgical assistance system that can utilize AI deep learning technology by incorporating it into a robotic surgical device.
Unlike open surgery, which cuts the surgical site enough to fit a doctor's hand and furniture, robotic surgery is performed using a small robotic arm of 8mm, and patient satisfaction is high in terms of beauty as well as effectiveness.
Because it uses a very small robotic arm, the practitioner needs training in sophisticated techniques. The research team created a surgical robot system equipped with AI deep learning technology for robotic surgery training. The AI model is an algorithm that extracts learning images every second from actual breast cancer robotic surgery images, learns thousands of images, and accurately predicts the skin plate incision boundary for surgery based on this.
Through real-time analysis according to the condition of the surgical patient, the incision boundary is provided very accurately, the surgical stability is increased, and the basis for judgment is presented to the surgeon.
In particular, the incision boundary presented by the AI model is expected to play a major role in reducing the risk of unnecessary tissue loss or complications that may occur during surgery, with results similar to those indicated directly by breast surgeons.
In the future, the research team will continue to learn breast cancer robotic surgery images in the newly developed AI model to increase the degree of completion.
Professor Park Hyung-seok said, `The demand for robotic surgery through minimally invasive surgery will continue to increase because breast cancer surgery sites can also be linked to women's self-esteem.' `We have developed a technology to effectively conduct robotic surgery training for new specialists.' The findings were published in the latest issue of the international journal `breast cancer research.'
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This article was translated by Naver AI translator.
