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About

Sachit Anand is a pioneering researcher at the intersection of artificial intelligence, pediatric surgery, and ergonomics. His work focuses on transforming surgical education and practice through AI-driven learning tools and robotic assistance. Anand’s most influential paper, “Artificial Intelligence in Surgical Learning” (40 citations), provides a concise review of AI’s potential to revolutionize surgical training, highlighting both its promise and the challenges of clinical implementation. He has also made significant contributions to understanding learning curves in pediatric robot-assisted pyeloplasty (17 citations), offering systematic insights that guide training protocols for robotic surgeons. His comparative study on ergonomic risks during vesicoscopic versus robotic ureteric reimplantation (11 citations) addresses the critical issue of musculoskeletal disorders in minimally invasive surgery, advocating for safer surgical practices. Additionally, Anand used infodemiology to evaluate the COVID-19 pandemic’s impact on public interest in minimally invasive surgery (4 citations), demonstrating his innovative use of data analytics. With a growing citation record and a focus on practical, impactful research, Anand is shaping the future of surgical learning and patient safety.