Benefits, limits, and risks of ChatGPT in medicine.

IF 4.7 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Frontiers in Artificial Intelligence Pub Date : 2025-01-30 eCollection Date: 2025-01-01 DOI:10.3389/frai.2025.1518049
Jonathan A Tangsrivimol, Erfan Darzidehkalani, Hafeez Ul Hassan Virk, Zhen Wang, Jan Egger, Michelle Wang, Sean Hacking, Benjamin S Glicksberg, Markus Strauss, Chayakrit Krittanawong
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Abstract

ChatGPT represents a transformative technology in healthcare, with demonstrated impacts across clinical practice, medical education, and research. Studies show significant efficiency gains, including 70% reduction in administrative time for discharge summaries and achievement of medical professional-level performance on standardized tests (60% accuracy on USMLE, 78.2% on PubMedQA). ChatGPT offers personalized learning platforms, automated scoring, and instant access to vast medical knowledge in medical education, addressing resource limitations and enhancing training efficiency. It streamlines clinical workflows by supporting triage processes, generating discharge summaries, and alleviating administrative burdens, allowing healthcare professionals to focus more on patient care. Additionally, ChatGPT facilitates remote monitoring and chronic disease management, providing personalized advice, medication reminders, and emotional support, thus bridging gaps between clinical visits. Its ability to process and synthesize vast amounts of data accelerates research workflows, aiding in literature reviews, hypothesis generation, and clinical trial designs. This paper aims to gather and analyze published studies involving ChatGPT, focusing on exploring its advantages and disadvantages within the healthcare context. To aid in understanding and progress, our analysis is organized into six key areas: (1) Information and Education, (2) Triage and Symptom Assessment, (3) Remote Monitoring and Support, (4) Mental Healthcare Assistance, (5) Research and Decision Support, and (6) Language Translation. Realizing ChatGPT's full potential in healthcare requires addressing key limitations, such as its lack of clinical experience, inability to process visual data, and absence of emotional intelligence. Ethical, privacy, and regulatory challenges further complicate its integration. Future improvements should focus on enhancing accuracy, developing multimodal AI models, improving empathy through sentiment analysis, and safeguarding against artificial hallucination. While not a replacement for healthcare professionals, ChatGPT can serve as a powerful assistant, augmenting their expertise to improve efficiency, accessibility, and quality of care. This collaboration ensures responsible adoption of AI in transforming healthcare delivery. While ChatGPT demonstrates significant potential in healthcare transformation, systematic evaluation of its implementation across different healthcare settings reveals varying levels of evidence quality-from robust randomized trials in medical education to preliminary observational studies in clinical practice. This heterogeneity in evidence quality necessitates a structured approach to future research and implementation.

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ChatGPT 在医学中的益处、局限和风险。
ChatGPT代表了医疗保健领域的一项变革性技术,对临床实践、医学教育和研究产生了显著影响。研究显示了显著的效率提高,包括出院总结的管理时间减少了70%,在标准化测试中实现了医疗专业水平的表现(USMLE的准确率为60%,PubMedQA的准确率为78.2%)。ChatGPT为医学教育提供个性化学习平台、自动评分、即时获取海量医学知识,解决资源限制,提高培训效率。它通过支持分诊流程、生成出院摘要和减轻管理负担,简化了临床工作流程,使医疗保健专业人员能够更多地关注患者护理。此外,ChatGPT促进远程监测和慢性疾病管理,提供个性化建议,药物提醒和情感支持,从而弥合临床就诊之间的差距。它处理和综合大量数据的能力加快了研究工作流程,有助于文献综述、假设生成和临床试验设计。本文旨在收集和分析涉及ChatGPT的已发表研究,重点探讨其在医疗保健背景下的优势和劣势。为了帮助理解和进步,我们的分析分为六个关键领域:(1)信息和教育,(2)分类和症状评估,(3)远程监测和支持,(4)精神卫生保健援助,(5)研究和决策支持,(6)语言翻译。要实现ChatGPT在医疗保健领域的全部潜力,需要解决一些关键限制,例如缺乏临床经验、无法处理视觉数据以及缺乏情商。道德、隐私和监管方面的挑战使其整合进一步复杂化。未来的改进应该集中在提高准确性,开发多模态人工智能模型,通过情感分析提高同理心,以及防止人工幻觉。虽然ChatGPT不是医疗保健专业人员的替代品,但它可以作为强大的助手,增强他们的专业知识,以提高效率、可访问性和护理质量。这种合作确保了在转变医疗保健服务时负责任地采用人工智能。虽然ChatGPT在医疗保健转型中显示出巨大的潜力,但对其在不同医疗保健环境中实施的系统评估显示,从医学教育中的稳健随机试验到临床实践中的初步观察性研究,证据质量水平各不相同。这种证据质量的异质性需要对未来的研究和实施采取结构化的方法。
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
CiteScore
6.10
自引率
2.50%
发文量
272
审稿时长
13 weeks
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