Automated Generation of High-Quality Medical Simulation Scenarios Through Integration of Semi-Structured Data and Large Language Models

arXiv:2404.19713v1 Announce Type: new
Abstract: This study introduces a transformative framework for medical education by integrating semi-structured data with Large Language Models (LLMs), primarily OpenAIs ChatGPT3.5, to automate the creation of medical simulation scenarios. Traditionally, developing these scenarios was a time-intensive process with limited flexibility to meet diverse educational needs. The proposed approach utilizes AI to efficiently generate detailed, clinically relevant scenarios that are tailored to specific educational objectives. This innovation has significantly reduced the time and resources required for …

abstract arxiv automate automated chatgpt3 chatgpt3.5 cs.cl data education framework integration language language models large language large language models llms medical process quality simulation structured data study through type