利用提示工程试开发 "临床表现检查(CPX)练习聊天机器人

Jundong Kim, Hye-Yoon Lee, Ji-Hwan Kim, Chang-Eop Kim
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摘要

研究目的在韩国医学界强调能力本位教育的背景下,本研究旨在利用大型语言模型和提示工程,开发一个试用版的 CPX(临床表现考试)练习聊天机器人:方法:从韩国国立韩医学研究院获取标准化的患者场景,并将其转换为文本格式。方法:从韩国国立医学研究院获取标准患者场景并转换为文本格式,然后使用角色提示和少量提示技术进行提示工程。使用了 GPT-4 API,并使用 gradio 软件包创建了一个网络应用程序。为定量评估聊天机器人的性能制定了内部评估标准:结果:根据内部评估标准实施并评估了聊天机器人。聊天机器人的正确性和合规性相对较高。然而,在保密性和自然度方面还需要改进:本研究成功试用了 CPX 实践聊天机器人,揭示了在韩医学领域利用人工智能技术开发教育模型的潜力。此外,研究还发现了局限性,并为未来的发展方向提供了启示。
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Pilot Development of a 'Clinical Performance Examination (CPX) Practicing Chatbot' Utilizing Prompt Engineering
Objectives: In the context of competency-based education emphasized in Korean Medicine, this study aimed to develop a pilot version of a CPX (Clinical Performance Examination) Practicing Chatbot utilizing large language models with prompt engineering.Methods: A standardized patient scenario was acquired from the National Institute of Korean Medicine and transformed into text format. Prompt engineering was then conducted using role prompting and few-shot prompting techniques. The GPT-4 API was employed, and a web application was created using the gradio package. An internal evaluation criterion was established for the quantitative assessment of the chatbot's performance.Results: The chatbot was implemented and evaluated based on the internal evaluation criterion. It demonstrated relatively high correctness and compliance. However, there is a need for improvement in confidentiality and naturalness.Conclusions: This study successfully piloted the CPX Practicing Chatbot, revealing the potential for developing educational models using AI technology in the field of Korean Medicine. Additionally, it identified limitations and provided insights for future developmental directions.
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