Yuqing Cao

Columbia University

Papers

2

Total Citations

41

H-Index

2

About

Yuqing Cao is a rising researcher at the intersection of artificial intelligence and surgical innovation, with a primary focus on real-time surgical phase recognition and computer-assisted intervention. Her most impactful work centers on bringing AI directly into the operating room through edge computing, enabling low-latency analysis of surgical video without relying on cloud infrastructure. In her highly cited 2023 study, Cao demonstrated how edge computing can power real-time phase recognition during surgery, a breakthrough that promises to enhance workflow analysis and intraoperative decision-making. She further advanced this field by establishing an AI-based confirmatory baseline for surgical phase recognition in inguinal hernia repair, leveraging a dataset of 209 robotic-assisted laparoscopic videos to explore and benchmark competitive deep learning models. With her two most-cited papers accumulating over 40 citations within a year of publication, Cao is quickly establishing herself as a key contributor to the growing field of surgical data science. Her work not only validates the feasibility of automated video-based quality assessment but also lays the groundwork for scalable, real-time AI tools that could transform surgical training and patient safety.

Research Focus

Key Achievements

2
H-Index
2
Papers
41
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Bringing Artificial Intelligence to the operating room: edge computing for real-time surgical phase recognition
21 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 11
🏛 Institutions: Columbia University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago