Papers
3
Total Citations
11
H-Index
3
About
John A. Perrone is a researcher whose work bridges the fields of bariatric surgery and computer vision, demonstrating a unique interdisciplinary breadth. His primary contributions lie in robotic-assisted bariatric and foregut surgery, where he has focused on optimizing surgical outcomes. Notably, his 2023 study on staple line reinforcement following robotic sleeve gastrectomy, drawing from the MBSAQIP database, has garnered 5 citations, providing critical data on reducing postoperative complications. He has also advanced the understanding of hiatal hernia repairs, comparing outcomes with and without Collis gastroplasty in a 2021 study (3 citations), addressing key concerns about staple line leaks and long-term reflux symptoms. Earlier in his career, Perrone made significant contributions to visual perception and robotics. His 2016 work on estimating heading direction from monocular video sequences using biologically-based sensors (3 citations) offered a novel approach to self-motion estimation, relevant for autonomous vehicles. This dual expertise in clinical surgery and computational vision highlights Perrone’s ability to tackle complex problems across disciplines, making his research valuable for both medical practitioners and engineers seeking to improve patient outcomes and machine perception.
Research Focus
Key Achievements
Top Papers
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