In this episode of The ICHE Podcast, host Dr. David Calfee speaks with Dr. Daniel Morgan of the University of Maryland School of Medicine and Dr. Jorge Salinas of Stanford University School of Medicine about the use of artificial intelligence for surgical site infection surveillance. The conversation highlights findings from their recent studies evaluating AI-assisted approaches to surgical site infection detection, including considerations related to performance, limitations, and the safe use of protected health information.

“Generative artificial intelligence for surgical site infection surveillance”: https://www.cambridge.org/core/journals/infection-control-and-hospital-epidemiology/article/abs/generative-artificial-intelligence-for-surgical-site-infection-surveillance/7094A07CD043BD630DE3591AB2F01707

“Use of a large language model integrated within the electronic medical record for the evaluation of surgical site infections – Northern California, 2025”: https://www.cambridge.org/core/journals/infection-control-and-hospital-epidemiology/article/use-of-a-large-language-model-integrated-within-the-electronic-medical-record-for-the-evaluation-of-surgical-site-infections-northern-california-2025/F2AF14E965608BC25367474685DA3949#article

ICHE’s Artificial Intelligence Special Collection: https://www.cambridge.org/core/journals/infection-control-and-hospital-epidemiology/announcements/call-for-papers/special-joint-collection-the-role-of-artificial-intelligence-in-infection-prevention-antimicrobial-stewardship-and-healthcare-epidemiology