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ChatGPT:在低收入和中等收入国家部署的前景与挑战。

ChatGPT: promise and challenges for deployment in low- and middle-income countries.

作者信息

Wang Xiaofei, Sanders Hayley M, Liu Yuchen, Seang Kennarey, Tran Bach Xuan, Atanasov Atanas G, Qiu Yue, Tang Shenglan, Car Josip, Wang Ya Xing, Wong Tien Yin, Tham Yih-Chung, Chung Kevin C

机构信息

Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China.

Section of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA.

出版信息

Lancet Reg Health West Pac. 2023 Sep 15;41:100905. doi: 10.1016/j.lanwpc.2023.100905. eCollection 2023 Dec.

DOI:10.1016/j.lanwpc.2023.100905
PMID:37731897
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10507635/
Abstract

In low- and middle-income countries (LMICs), the fields of medicine and public health grapple with numerous challenges that continue to hinder patients' access to healthcare services. ChatGPT, a publicly accessible chatbot, has emerged as a potential tool in aiding public health efforts in LMICs. This viewpoint details the potential benefits of employing ChatGPT in LMICs to improve medicine and public health encompassing a broad spectrum of domains ranging from health literacy, screening, triaging, remote healthcare support, mental health support, multilingual capabilities, healthcare communication and documentation, medical training and education, and support for healthcare professionals. Additionally, we also share potential concerns and limitations associated with the use of ChatGPT and provide a balanced discussion on the opportunities and challenges of using ChatGPT in LMICs.

摘要

在低收入和中等收入国家(LMICs),医学和公共卫生领域面临着诸多挑战,这些挑战持续阻碍着患者获得医疗服务。ChatGPT是一款公众可访问的聊天机器人,已成为协助低收入和中等收入国家公共卫生工作的潜在工具。这一观点详细阐述了在低收入和中等收入国家使用ChatGPT改善医学和公共卫生的潜在益处,涵盖了从健康素养、筛查、分诊、远程医疗支持、心理健康支持、多语言能力、医疗沟通与记录、医学培训与教育以及对医疗专业人员的支持等广泛领域。此外,我们还分享了与使用ChatGPT相关的潜在担忧和局限性,并对在低收入和中等收入国家使用ChatGPT的机遇与挑战进行了全面讨论。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/3d3270f77fbc/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/0f5531794664/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/b587578cc5ab/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/fb42a44875f0/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/c4e904d750ff/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/3d3270f77fbc/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/0f5531794664/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/b587578cc5ab/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/fb42a44875f0/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/c4e904d750ff/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83e2/10507635/3d3270f77fbc/gr5.jpg

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