Impact of Generative AI on Operative Planning in Otolaryngology Residents

Sholem Hack, Daor Hayu, Jacon E. Karni, Eran Glikson, Eric Remer, Eran E. Alon, Omar G. Ahmed, Masayoshi Takashima, City St, s University of London, School of Medicine, Program Delivered By University of Nicosia at the Chaim Sheba Medical Center, Ramat Gan, st Faculty of Medicine, Charles University in, Czech Republic, Washington University in St, Department of Otolaryngology, Sheba Medical Center, Ramat Gan, Gray Faculty of Medical , Health Sciences, Tel-Aviv University, Tel aviv, Department of Otolaryngology-Head and Neck Surgery, Houston Methodist Hospital

Surgical Innovation

Published online on April 29, 2026

Abstract

Surgical Innovation, Ahead of Print.
PurposeTo quantify how large language model (LLM) assistance influences otolaryngology residents’ operative planning in a simulation-based setting.MethodsIn a within-subjects paired design, 13 otolaryngology residents (PGY1-4) completed 21 synthetic ...