Yasmina Al Khalil
Papers
5
Total Citations
11
H-Index
2
About
Yasmina Al Khalil is a researcher at the forefront of surgical data science, with a primary focus on advancing robotic-assisted minimally invasive esophagectomy (RAMIE) for esophageal cancer treatment. Her work centers on developing and benchmarking deep learning models for real-time surgical phase recognition, instrument keypoint estimation, and anatomy segmentation—critical components for improving intraoperative guidance and surgical training. Notably, she led the organization of the PhaKIR 2024 challenge, a landmark comparative validation of state-of-the-art methods in endoscopy, demonstrating her leadership in the field. Her most cited paper (2025) proposes a framework for benchmarking surgical phase recognition models, while another key study critically evaluates whether standard segmentation metrics reflect clinical reality—a question of high practical importance. With over a dozen citations across her early-career publications, Al Khalil’s work is already shaping how AI systems are validated for real-world surgical use. She also contributed to educational robotics, co-authoring a framework for teaching robotic control via a visual programming language. Her research bridges technical rigor and clinical relevance, making her a rising voice in surgical AI.
Research Focus
Key Achievements
Top Papers
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