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评估 ChatGPT 在解决有关运动康复中聊天机器人使用的跨学科问题方面的能力:模拟研究。

Assessing ChatGPT's Competency in Addressing Interdisciplinary Inquiries on Chatbot Uses in Sports Rehabilitation: Simulation Study.

机构信息

Department of Microbiology, Immunology, & Cell Biology, West Virginia University, Morgantown, WV, United States.

Department of Chemical and Biomedical Engineering, West Virginia University, Morgantown, WV, United States.

出版信息

JMIR Med Educ. 2024 Aug 7;10:e51157. doi: 10.2196/51157.

Abstract

BACKGROUND

ChatGPT showcases exceptional conversational capabilities and extensive cross-disciplinary knowledge. In addition, it can perform multiple roles in a single chat session. This unique multirole-playing feature positions ChatGPT as a promising tool for exploring interdisciplinary subjects.

OBJECTIVE

The aim of this study was to evaluate ChatGPT's competency in addressing interdisciplinary inquiries based on a case study exploring the opportunities and challenges of chatbot uses in sports rehabilitation.

METHODS

We developed a model termed PanelGPT to assess ChatGPT's competency in addressing interdisciplinary topics through simulated panel discussions. Taking chatbot uses in sports rehabilitation as an example of an interdisciplinary topic, we prompted ChatGPT through PanelGPT to role-play a physiotherapist, psychologist, nutritionist, artificial intelligence expert, and athlete in a simulated panel discussion. During the simulation, we posed questions to the panel while ChatGPT acted as both the panelists for responses and the moderator for steering the discussion. We performed the simulation using ChatGPT-4 and evaluated the responses by referring to the literature and our human expertise.

RESULTS

By tackling questions related to chatbot uses in sports rehabilitation with respect to patient education, physiotherapy, physiology, nutrition, and ethical considerations, responses from the ChatGPT-simulated panel discussion reasonably pointed to various benefits such as 24/7 support, personalized advice, automated tracking, and reminders. ChatGPT also correctly emphasized the importance of patient education, and identified challenges such as limited interaction modes, inaccuracies in emotion-related advice, assurance of data privacy and security, transparency in data handling, and fairness in model training. It also stressed that chatbots are to assist as a copilot, not to replace human health care professionals in the rehabilitation process.

CONCLUSIONS

ChatGPT exhibits strong competency in addressing interdisciplinary inquiry by simulating multiple experts from complementary backgrounds, with significant implications in assisting medical education.

摘要

背景

ChatGPT 展示了出色的对话能力和广泛的跨学科知识。此外,它可以在单个聊天会话中扮演多种角色。这种独特的多角色扮演功能使 ChatGPT 成为探索跨学科主题的有前途的工具。

目的

本研究旨在评估 ChatGPT 在解决跨学科问题方面的能力,方法是通过案例研究探讨聊天机器人在运动康复中的应用机会和挑战来评估 ChatGPT。

方法

我们开发了一个名为 PanelGPT 的模型,通过模拟小组讨论来评估 ChatGPT 解决跨学科主题的能力。以聊天机器人在运动康复中的应用为例,我们通过 PanelGPT 提示 ChatGPT 在模拟小组讨论中扮演物理治疗师、心理学家、营养师、人工智能专家和运动员的角色。在模拟过程中,我们向小组提出问题,而 ChatGPT 则作为小组回答和引导讨论的主持人。我们使用 ChatGPT-4 进行模拟,并通过参考文献和我们的人类专业知识来评估回复。

结果

通过针对与运动康复中使用聊天机器人相关的问题进行讨论,涉及患者教育、物理治疗、生理学、营养和伦理考虑,ChatGPT 模拟小组讨论的回复合理地指出了各种好处,例如 24/7 支持、个性化建议、自动跟踪和提醒。ChatGPT 还正确强调了患者教育的重要性,并指出了一些挑战,例如交互模式有限、情感相关建议不准确、确保数据隐私和安全、数据处理透明度和模型训练公平性。它还强调,聊天机器人应该作为副驾驶协助,而不是在康复过程中取代人类医疗保健专业人员。

结论

ChatGPT 通过模拟来自互补背景的多个专家来展示在解决跨学科探究方面的强大能力,这对辅助医学教育具有重要意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f77a/11339563/50c16507fa56/mededu_v10i1e51157_fig1.jpg

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