Large language models in laparoscopic surgery: A transformative opportunity

Abstract

This opinion paper explores the transformative potential of large language models (LLMs) in laparoscopic surgery and argues for their integration to enhance surgical education, decision support, reporting, and patient care. LLMs can revolutionize surgical education by providing personalized learning experiences and accelerating skill acquisition. Intelligent decision support systems powered by LLMs can assist surgeons in making complex decisions, optimizing surgical workflows, and improving patient outcomes. Moreover, LLMs can automate surgical reporting and generate personalized patient education materials, streamlining documentation and improving patient engagement. However, challenges such as data scarcity, surgical semantic capture, real-time inference, and integration with existing systems need to be addressed for successful LLM integration. The future of laparoscopic surgery lies in the seamless integration of LLMs, enabling autonomous robotic surgery, predictive surgical planning, intraoperative decision support, virtual surgical assistants, and continuous learning. By harnessing the power of LLMs, laparoscopic surgery can be transformed, empowering surgeons and ultimately benefiting patients.

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