Zixuan Xiang
Papers
2
Total Citations
41
H-Index
2
About
Zixuan Xiang is pioneering the integration of artificial intelligence into minimally invasive surgery, with a focus on real-time surgical phase recognition. His work centers on bringing AI directly to the operating room through edge computing, enabling automated, low-latency analysis of surgical workflows. Xiang’s most cited research, including his 2023 study on edge computing for real-time surgical phase recognition (21 citations), demonstrates how computer vision and deep learning can transform video-recorded robotic-assisted surgeries into tools for quality assessment and workflow optimization. In a complementary study (20 citations), he established a robust AI-based baseline for surgical phase recognition in inguinal hernia repair, analyzing 209 robotic-assisted laparoscopic videos to validate competitive deep learning models. These contributions have significant implications for improving surgical training, enhancing patient safety, and enabling data-driven operational efficiency. By bridging the gap between cutting-edge AI and clinical practice, Xiang is helping to define a new standard for intelligent, real-time surgical assistance.
Research Focus
Key Achievements
Top Papers
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- 2