Kaan Yarali

Columbia University

Papers

2

Total Citations

41

H-Index

2

About

Kaan Yarali is a pioneering researcher at the intersection of artificial intelligence and surgical medicine, with a primary focus on real-time surgical phase recognition and computer vision in the operating room. His groundbreaking work demonstrates how AI and deep learning can transform surgical workflow analysis, particularly through edge computing solutions that bring intelligent processing directly to the operating theater. Yarali’s most impactful contributions include developing AI-based confirmatory baselines for surgical phase recognition in robotic-assisted procedures, notably his work on inguinal hernia repair using a substantial dataset of 209 video-recorded surgeries. His 2023 publications have already accumulated over 40 citations, reflecting the field’s urgent need for automated quality assessment tools. By enabling real-time analysis of surgical video streams, Yarali’s research paves the way for improved surgical training, enhanced patient safety, and more efficient operating room workflows. His work represents a critical step toward the practical integration of artificial intelligence into everyday surgical practice, making complex procedures safer and more standardized through the power of machine learning.

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 · 14 days ago