Saad A Shebrain
Papers
1
Total Citations
2
H-Index
1
About
Dr. Saad A. Shebrain is a leading figure in surgical education and simulation-based training, with a focused expertise in laparoscopic surgery and objective performance assessment. His research centers on integrating artificial intelligence and computer vision into surgical skills evaluation, addressing the critical need for unbiased, automated feedback in training environments. Dr. Shebrain’s major contribution includes pioneering the application of hybrid deep learning models—such as YOLOv8 combined with instance segmentation—to distinguish sealed tissue and detect tool tips within Fundamentals of Laparoscopic Surgery (FLS) box trainers. This work, published in 2023, directly tackles the time-intensive and subjective nature of traditional surgeon-led assessments, offering a scalable solution for real-time, objective skill evaluation. While his most cited paper currently holds 2 citations, its innovative approach to automating intracorporeal suturing assessment positions it as a foundational contribution to the emerging field of AI-assisted surgical coaching. Dr. Shebrain’s research is instrumental in advancing competency-based surgical education, promising to reduce evaluator bias and enhance training efficiency for future surgeons.
Research Focus
Key Achievements
Top Papers
- 1