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与 ChatGPT 交心:患者咨询 AI 提供心血管健康建议的影响。

Heart-to-heart with ChatGPT: the impact of patients consulting AI for cardiovascular health advice.

机构信息

Department of Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark.

Department of Business and Management, University of Southern Denmark Faculty of Business and Social Sciences, Odense, Denmark.

出版信息

Open Heart. 2023 Nov;10(2). doi: 10.1136/openhrt-2023-002455.

Abstract

OBJECTIVES

The advent of conversational artificial intelligence (AI) systems employing large language models such as ChatGPT has sparked public, professional and academic debates on the capabilities of such technologies. This mixed-methods study sets out to review and systematically explore the capabilities of ChatGPT to adequately provide health advice to patients when prompted regarding four topics from the field of cardiovascular diseases.

METHODS

As of 30 May 2023, 528 items on PubMed contained the term ChatGPT in their title and/or abstract, with 258 being classified as journal articles and included in our thematic state-of-the-art review. For the experimental part, we systematically developed and assessed 123 prompts across the four topics based on three classes of users and two languages. Medical and communications experts scored ChatGPT's responses according to the 4Cs of language model evaluation proposed in this article: correct, concise, comprehensive and comprehensible.

RESULTS

The articles reviewed were fairly evenly distributed across discussing how ChatGPT could be used for medical publishing, in clinical practice and for education of medical personnel and/or patients. Quantitatively and qualitatively assessing the capability of ChatGPT on the 123 prompts demonstrated that, while the responses generally received above-average scores, they occupy a spectrum from the concise and correct via the absurd to what only can be described as hazardously incorrect and incomplete. Prompts formulated at higher levels of health literacy generally yielded higher-quality answers. Counterintuitively, responses in a lower-resource language were often of higher quality.

CONCLUSIONS

The results emphasise the relationship between prompt and response quality and hint at potentially concerning futures in personalised medicine. The widespread use of large language models for health advice might amplify existing health inequalities and will increase the pressure on healthcare systems by providing easy access to many seemingly likely differential diagnoses and recommendations for seeing a doctor for even harmless ailments.

摘要

目的

采用大型语言模型(如 ChatGPT)的会话式人工智能系统的出现引发了公众、专业人士和学术界对这些技术能力的辩论。本混合方法研究旨在回顾和系统地探讨 ChatGPT 在提示心血管疾病领域的四个主题时,为患者提供足够的健康建议的能力。

方法

截至 2023 年 5 月 30 日,PubMed 中 528 项标题和/或摘要中包含 ChatGPT 一词,其中 258 项被归类为期刊文章并包含在我们的主题综述中。对于实验部分,我们根据三类用户和两种语言,系统地开发和评估了四个主题的 123 个提示。医学和传播专家根据本文提出的语言模型评估的 4C 标准(正确、简洁、全面和可理解)对 ChatGPT 的回答进行评分。

结果

综述文章在讨论 ChatGPT 如何用于医学出版、临床实践以及医学人员和/或患者教育方面分布较为均匀。对 123 个提示的能力进行定量和定性评估表明,虽然这些回答通常得分较高,但它们的范围从简洁和正确到荒谬再到只能被描述为危险不正确和不完整。以更高健康素养水平制定的提示通常会产生更高质量的答案。出人意料的是,资源较少的语言的回答往往质量更高。

结论

结果强调了提示和响应质量之间的关系,并暗示了个性化医学中可能令人担忧的未来。大型语言模型在健康建议方面的广泛应用可能会放大现有的健康不平等现象,并通过为许多看似可能的鉴别诊断和建议去看医生提供便捷途径,从而增加对医疗系统的压力,即使是无害的疾病。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b2d/10649823/fea2fe323b80/openhrt-2023-002455f01.jpg

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