Micaela M. Esquivel
Papers
1
Total Citations
47
H-Index
1
About
Micaela M. Esquivel is a pioneering researcher at the intersection of artificial intelligence, computer vision, and surgical robotics. Her work focuses on developing objective, data-driven methods to assess technical proficiency in robotic surgery, moving beyond traditional subjective evaluations. Her most-cited paper, "Using AI and computer vision to analyze technical proficiency in robotic surgery" (2022, 47 citations), introduces a novel framework that leverages machine learning algorithms to automatically analyze surgical video data, identifying key performance metrics and skill levels. This contribution has significant implications for surgical training, credentialing, and quality assurance, offering a scalable and unbiased tool to enhance patient safety. Esquivel’s research is notable for bridging the gap between advanced computational techniques and practical clinical applications, positioning her as a leader in the emerging field of AI-assisted surgical assessment. Her work has already influenced how surgical educators and institutions approach skill evaluation, and her ongoing efforts promise to further integrate intelligent systems into the operating room, ultimately improving surgical outcomes worldwide.
Research Focus
Key Achievements
Top Papers
- 1