Leap Rail, an artificial intelligence platform for operating room performance, today announced that Founder and Chief Executive Officer Shayan Zadeh has authored a chapter in the newly released third edition of Operating Room Leadership and Perioperative Practice Management, published by Cambridge University Press (ISBN 978-1009467407).
Edited by Alan David Kaye, Richard D. Urman, and Charles J. Fox III, the textbook is widely recognized as a comprehensive academic reference on perioperative leadership. The third edition is the first to dedicate a chapter to artificial intelligence in the OR. Shayan Zadeh’s contribution, Chapter 17, titled “The Role of Artificial Intelligence in Transforming Operating Room Performance,” provides perioperative leaders with a structured overview of four AI technology categories — machine learning and predictive analytics, computer vision, robotics, and natural language processing — and across the operational areas where these technologies are producing change today.
The chapter walks through the operational applications already producing measurable change in the OR: scheduling and resource allocation; inventory and supply chain management, including preference card optimization; staffing and personnel management; and the OR business manager role, where generative AI is now equipped to synthesize the high-volume, multi-source data the role depends on. It also examines training and education applications, including VR/AR-based simulation and AI-assisted assessment of technical and non-technical surgical skills. The chapter closes with a substantive discussion of ethical considerations — patient consent, data security, algorithmic bias — and an honest treatment of the constraints that face AI adoption in healthcare, including data quality and interoperability problems, regulatory complexity, and the cost and ROI calculus that frames every health-system technology decision.
“Cambridge University Press dedicated this chapter to AI for a specific reason — the field has moved past the point where perioperative leaders can engage AI only when they happen to be evaluating a vendor,” said Shayan Zadeh, Founder and CEO of Leap Rail. “The chapter is a primer for the perioperative leaders who are now making decisions about scheduling, staffing, training, and governance under that reality. I am grateful for the opportunity to contribute to this project and to the editors for the depth they gave the topic in this edition.”
The chapter draws on a body of work that Shayan and Leap Rail have contributed to the perioperative field over several years. It cites Shayan’s own co-authored peer-reviewed research, Tuwatananuraket al. (2019), “Machine Learning Can Improve Estimation of Surgical Case Duration: A Pilot Study,” published in the Journal of Medical Systems (PMID 30656433).
Recently, Shayan joined perioperative leaders from Baptist Health Care and Northbay Medical Center on the First Case Podcast for “Data-Driven Surgery: Empowering Confidence and Precision,” a conversation focused on the operational realities of AI in daily OR practice.
Leap Rail’s published outcomes — a 70%improvement in case-duration prediction accuracy compared with average estimates in the EHR, up to $50,000 in annual labor savings per 20-room OR, a20% reduction in preventable surgical cancellations, and a 15% improvement in block utilization — have been documented in industry venues, includingHealthcare Tech Outlook, which named Leap Rail a “Top Operating Room ManagementTechnology Company” in 2018.
Leap Rail was founded in 2016 out of the MIT Grand Hack, where Shayan worked alongside practicing anesthesiologists and operating room nurses on the original concept. The platform analyzes more than 1,500 unique data dimensions per case to support surgical scheduling, block utilization, perioperative communication, patient engagement, and analytics for hospitals and health systems across the United States.
The third edition of Operating Room Leadership and Perioperative Practice Management is available from Cambridge University Press at cambridge.org and through academic booksellers.
About Shayan Zadeh
Shayan Zadeh is the Founder and Chief Executive Officer of Leap Rail. He is a co-author of Tuwatananurak et al.(2019), “Machine Learning Can Improve Estimation of Surgical Case Duration: A Pilot Study,” published in the Journal of Medical Systems. He previously co-founded Zoosk, the consumer technology company that scaled to more than $200M in annual revenue before its acquisition by Spark Networks for $258M. Shayan holds eight U.S. patents, a Master of Science in Computer Science from the University of Maryland, and an MBA from the University of Washington. He is an inductee of the University of Maryland Alumni Hall of Fame.
About Leap Rail
Leap Rail is an artificial intelligence platform that helps hospitals and health systems run more predictable, efficient, and patient-centered operating rooms. Founded in 2016 and headquartered in Houston, Texas, Leap Rail applies AI and machine learning to surgical scheduling, block utilization, perioperative communication, patient engagement, supply chain coordination, and OR analytics. The platform is SOC 2 certified and HIPAA compliant and integrates with major EHR systems.