Artificial intelligence in asthma health literacy: a comparative analysis of ChatGPT versus Gemini.

IF 1.3 4区 医学 Q3 ALLERGY
Journal of Asthma Pub Date : 2025-09-01 Epub Date: 2025-04-26 DOI:10.1080/02770903.2025.2495729
Simon Høj, Vibeke Backer, Charlotte Suppli Ulrik, Torben Sigsgaard, Howraman Meteran
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引用次数: 0

Abstract

Background: Asthma is a complex and heterogeneous chronic disease affecting over 300 million individuals worldwide. Despite advances in pharmacotherapy, poor disease control remains a major challenge, necessitating innovative approaches to patient education and self-management. Artificial intelligence driven chatbots, such as ChatGPT and Gemini, have the potential to enhance asthma care by providing real-time, evidence-based information. As asthma management moves toward personalized medicine, AI could support individualized education and treatment guidance. However, concerns remain regarding the accuracy and reliability of AI-generated medical content.

Objective: This study evaluated the accuracy of ChatGPT (version 4.0) and Gemini (version 1.2) in providing asthma-related health information using the Patient-completed Asthma Knowledge Questionnaire, a validated asthma literacy tool.

Methods: A cross-sectional study was conducted in which both AI models answered 54 standardized asthma-related items. Responses were classified as correct or incorrect based on alignment with validated clinical knowledge. Accuracy was assessed using descriptive statistics, Cohen's kappa for inter-model agreement, and chi-square tests for comparative performance.

Results: ChatGPT achieved an accuracy of 96.3% (52/54 correct; 95% CI: 87.5%-99.0%), while Gemini scored 92.6% (50/54 correct; 95% CI: 82.5%-97.1%), with no statistically significant difference (p = 0.67). Cohen's kappa demonstrated near-perfect agreement for ChatGPT (κ = 0.91) and strong agreement for Gemini (κ = 0.82).

Conclusion: ChatGPT and Gemini demonstrated high accuracy in delivering asthma-related health information, supporting their potential as adjunct tools for patient education. AI models could potentially play a role in personalized asthma management by providing tailored treatment guidance and improving patient engagement.

人工智能对哮喘健康素养的影响:ChatGPT与Gemini的比较分析。
背景:哮喘是一种复杂的异质性慢性疾病,影响全球超过3亿人。尽管在药物治疗方面取得了进展,但疾病控制不力仍然是一个重大挑战,需要采用创新方法对患者进行教育和自我管理。人工智能驱动的聊天机器人,如ChatGPT和Gemini,有可能通过提供实时的、基于证据的信息来加强哮喘治疗。随着哮喘管理向个性化医疗发展,人工智能可以支持个性化教育和治疗指导。然而,人工智能生成的医疗内容的准确性和可靠性仍然令人担忧。目的:本研究评估ChatGPT(版本4.0)和Gemini(版本1.2)在使用患者完成的哮喘知识问卷(一种经过验证的哮喘素养工具)提供哮喘相关健康信息方面的准确性。方法:采用横断面研究,两种人工智能模型均回答了54项标准化哮喘相关问题。根据与经过验证的临床知识的一致性,将反应分为正确或不正确。准确性评估使用描述性统计,科恩kappa模型间的一致性,卡方检验比较性能。结果:ChatGPT的准确率为96.3%(52/54正确;95% CI: 87.5%-99.0%),而双子座得分为92.6%(50/54正确;95% CI: 82.5% ~ 97.1%),差异无统计学意义(p = 0.67)。Cohen的kappa证明了ChatGPT (κ = 0.91)和Gemini (κ = 0.82)的近乎完美的一致性。结论:ChatGPT和Gemini在提供哮喘相关健康信息方面表现出较高的准确性,支持它们作为患者教育辅助工具的潜力。人工智能模型可以通过提供量身定制的治疗指导和提高患者参与度,在个性化哮喘管理中发挥作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Asthma
Journal of Asthma 医学-过敏
CiteScore
4.00
自引率
5.30%
发文量
158
审稿时长
3-8 weeks
期刊介绍: Providing an authoritative open forum on asthma and related conditions, Journal of Asthma publishes clinical research around such topics as asthma management, critical and long-term care, preventative measures, environmental counselling, and patient education.
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