Augmenting Surgical Preparation: How Learners Use Artificial Intelligence to Prepare for the Operating Room

Area of Science:

• Medical Education
• Artificial Intelligence in Surgery
• Surgical Training Technologies

Background:

• Surgical trainees increasingly use large language models (LLMs) for preparation.
• Limited understanding exists on how AI is specifically used for surgical competence.
• Rapid AI advancements challenge educators' awareness of available systems and best practices.

Purpose of the Study:

• To explore custom learning tools created by LLMs for surgical preparation.
• To demonstrate principles for effective LLM utilization in surgical education.
• To address current limitations and promote active learning with AI.

Main Methods:

• Discussed custom learning tools applicable to surgical preparation scenarios.
• Demonstrated three key principles for successful LLM use: LLM selection, goal clarity, and context provision.
• Analyzed limitations such as AI hallucinations, bias, and sycophancy.

Main Results:

• LLMs can be leveraged to create tailored surgical preparation tools.
• Effective LLM use requires strategic selection, defined learning objectives, and adequate contextual information.
• Identified critical limitations including AI-generated inaccuracies and biases.

Conclusions:

• Optimizing LLM use shifts the paradigm from passive information retrieval to active, engaged learning.
• Aimed to make AI systems more accessible for educators and encourage learners to develop custom AI tools.
• Promoted a more dynamic and effective approach to surgical training through AI integration.