ChatGPT作为医疗保健服务和研究工具的进展、接受和潜力:系统综述

IF 1.9
Navkaran Singh, Samantha Neubronner, Suren Kanayan, Sebastian Illanes, Mahesh Choolani, Matthew Warren Kemp
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引用次数: 0

摘要

摘要:ChatGPT因其在自然语言处理中的能力而受到广泛关注,它使机器能够评估人类语言输入并生成复杂但不断发展的答案。随着大型语言模型(llm)的不断发展,需要明确的指导方针来帮助医疗保健提供者和教育工作者最大化其利益,同时降低潜在风险。这篇综述评估了ChatGPT在医疗保健援助中的效用和准确性,特别是在理解临床知识和指导临床实践和研究方面。从2022年11月30日(ChatGPT的发布日期)到2024年3月14日,在PubMed/MEDLINE上搜索ChatGPT相关的文章,得到2690篇文章。经过筛选和审查,2141篇文章被认为与临床和研究领域相关。在这些文章中,60.3%的人支持ChatGPT,强调了它在自动化日常任务、增强决策过程和解决医疗保健领域复杂挑战方面的巨大潜力。然而,考虑到尚未解决的道德问题以及对准确性、偏见、隐私和法律的担忧,0.9%的人不支持以目前的形式使用ChatGPT。此外,38.8%的受访者持模棱两可的态度,建议进一步研究,以充分了解ChatGPT在医疗保健领域快速发展的能力和潜在影响。这篇综述提出了一个新创建的概念框架,“ABCD模型”,以促进研究人员和医疗保健从业者的系统方法来导航ChatGPT的优势和局限性。该模型旨在通过提供指导原则来协调ChatGPT的开发和部署,ChatGPT和其他新兴法学硕士应将其纳入进一步的开发中,以确保其在医疗保健领域的适当应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advances, reception and potential of ChatGPT as a tool for healthcare delivery and research: a systematic review.

Abstract: ChatGPT gained widespread attention for its capabilities in natural language processing, enabling machines to assess human language inputs and generate complex, yet evolving answers. As large language models (LLMs) continue to develop, clear guidelines are needed to help healthcare providers and educators maximise their benefits while mitigating potential risks. This review assessed the utility and accuracy of applying ChatGPT in healthcare assistance, specifically in understanding clinical knowledge and guiding clinical practice and research. A search on PubMed/MEDLINE for ChatGPT-related articles from 30 November 2022 (ChatGPT's release date) to 14 March 2024 yielded 2690 articles. After screening and reviewing, 2141 articles were deemed relevant to the clinical and research domains. Of the articles, 60.3% were supportive of ChatGPT, highlighting its immense potential for automating routine tasks, enhancing decision-making processes and addressing complex challenges in health care. However, 0.9% were not supportive of ChatGPT's utilisation in its current form, given the unresolved ethical implications and concerns regarding accuracy, bias, privacy and legal. Additionally, 38.8% had an equivocal stance, suggesting for further research to fully understand the rapidly evolving capabilities and potential impacts of ChatGPT in healthcare. This review presents a newly created conceptual framework, the 'ABCD model', to facilitate a systematic approach for researchers and healthcare practitioners to navigate ChatGPT's strengths and limitations. The model aims to align the development and deployment of ChatGPT by providing guiding principles, which ChatGPT and other emerging LLMs should incorporate into further developments to ensure their suitable application in health care.

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