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About

Dr. Shunming Hong is a leading researcher at the intersection of artificial intelligence and robotic surgery, with a primary focus on vascular interventional surgery (VIS). His work addresses the critical challenge of enhancing precision and safety in minimally invasive procedures for cardiovascular and cerebrovascular diseases. Dr. Hong’s major contributions include pioneering machine learning frameworks for objective surgical skill assessment, as demonstrated in his highly cited 2020 paper (48 citations), which introduced a vascular difficulty index to quantify operator proficiency. He further advanced the field with the development of “Surgical GAN” (30 citations), a generative adversarial network enabling real-time path planning for passive flexible tools in endovascular surgeries. Additionally, his 2019 study (29 citations) on non-interference operation detection for master-slave VIS robot systems has been instrumental in improving surgical outcomes by ensuring seamless human-robot collaboration. Through these innovations, Dr. Hong has established himself as a key figure in translating AI-driven automation into tangible clinical benefits, with his work collectively garnering over 100 citations and shaping the future of intelligent, robot-assisted vascular interventions.