ChatGPT: promise and challenges for deployment in low- and middle-income countries
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 LMIC...
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| Published in: | The Lancet regional health. Western Pacific Vol. 41; p. 100905 |
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| Main Authors: | , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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England
Elsevier Ltd
01-12-2023
Elsevier |
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| Online Access: | Get full text |
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| 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. |
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| AbstractList | 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. 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.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. |
| ArticleNumber | 100905 |
| Author | Wang, Ya Xing Qiu, Yue Atanasov, Atanas G. Car, Josip Sanders, Hayley M. Liu, Yuchen Seang, Kennarey Chung, Kevin C. Tham, Yih-Chung Wang, Xiaofei Tran, Bach Xuan Tang, Shenglan Wong, Tien Yin |
| Author_xml | – sequence: 1 givenname: Xiaofei surname: Wang fullname: Wang, Xiaofei organization: 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 – sequence: 2 givenname: Hayley M. surname: Sanders fullname: Sanders, Hayley M. organization: Section of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA – sequence: 3 givenname: Yuchen surname: Liu fullname: Liu, Yuchen organization: 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 – sequence: 4 givenname: Kennarey surname: Seang fullname: Seang, Kennarey organization: Grant Management Office, University of Health Sciences, Phnom Penh, Cambodia – sequence: 5 givenname: Bach Xuan surname: Tran fullname: Tran, Bach Xuan organization: Department of Health Economics, Institute for Preventive Medicine and Public Health, Hanoi Medical University, Hanoi, Vietnam – sequence: 6 givenname: Atanas G. surname: Atanasov fullname: Atanasov, Atanas G. organization: Ludwig Boltzmann Institute Digital Health and Patient Safety, Medical University of Vienna, Spitalgasse 23, 1090, Vienna, Austria – sequence: 7 givenname: Yue surname: Qiu fullname: Qiu, Yue organization: Institute for Hospital Management, Tsinghua University, Beijing, China – sequence: 8 givenname: Shenglan surname: Tang fullname: Tang, Shenglan organization: Duke Global Health Institute, Duke University, Durham, NC, USA – sequence: 9 givenname: Josip orcidid: 0000-0001-8969-371X surname: Car fullname: Car, Josip organization: Centre for Population Health Sciences, Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore – sequence: 10 givenname: Ya Xing surname: Wang fullname: Wang, Ya Xing organization: Beijing Institute of Ophthalmology, Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China – sequence: 11 givenname: Tien Yin orcidid: 0000-0002-8448-1264 surname: Wong fullname: Wong, Tien Yin organization: Singapore Eye Research Institute, Singapore National Eye Centre, Singapore – sequence: 12 givenname: Yih-Chung orcidid: 0000-0002-6752-797X surname: Tham fullname: Tham, Yih-Chung email: thamyc@nus.edu.sg organization: Singapore Eye Research Institute, Singapore National Eye Centre, Singapore – sequence: 13 givenname: Kevin C. surname: Chung fullname: Chung, Kevin C. email: kecchung@med.umich.edu organization: Section of Plastic Surgery, Department of Surgery, University of Michigan Medical School, Ann Arbor, MI, USA |
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| Keywords | Low to middle income countries Equity Global health Large language model ChatGPT Public health |
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