About

Ozanan R. Meireles stands at the forefront of surgical artificial intelligence and minimally invasive surgery, pioneering the integration of machine learning into the modern operating room. His most influential work, a 2017 paper on automated real-time video segmentation of laparoscopic and robotic surgeries (65 citations), established a foundation for context-aware surgical AI capable of improving perioperative workflows and surgical education. Building on this, Meireles has advanced predictive surgical intelligence through contributions like SUPR-GAN, a generative model designed to anticipate future surgical events rather than merely cataloging past ones — a conceptual leap with profound implications for intraoperative decision support and risk mitigation. Beyond AI, Meireles has shaped surgical training and practice on a global scale, contributing to a worldwide Delphi consensus on robotic-assisted esophagectomy curricula and authoring expert consensus statements on AI's role in metabolic and bariatric surgery. His work examining the economic realities of robotic surgery reflects a commitment to accessibility alongside innovation. As a founding voice in the SAGES AI task force, he has helped define how operating room data is captured and standardized. Collectively, his research bridges surgical science, computer vision, and health systems thinking — making him a defining figure in the future of intelligent surgery.

Research Focus

Key Achievements

8
H-Index
13
Papers
235
Total Citations
18
Avg Citations/Paper
🏆 Most Cited Paper
Machine learning and coresets for automated real-time video segmentation of laparoscopic and robot-assisted surgery
65 citations · 2017
📈 Most Prolific Year: 2025 (3 Papers)
🤝 Key Collaborators: 163
🏛 Institutions: Massachusetts General Hospital, Boston University, University of California San Diego, University College Dublin, Artificial Intelligence in Medicine (Canada)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago