Principles to guide the effective use of technology to support capacity development in global health partnerships

Lynch, Marion; Yoo, Ji-Hoon; Mukami, Diana; Arian, Waheed; Bashford, Tom; Hobden, Paul; Luthra, Pramod; Patel, Mumtaz; Ralph, Neil; Winters, Niall; McGrath, Louise; Simms, Ben

doi:10.1136/bmjgh-2021-006783

Cited by 2 publications

(1 citation statement)

References 35 publications

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“…In the present paper, we will explore how new technological and digital tools can help address clinical public and global health needs in the Global South [1,2], leveraging and capitalizing on our experience with the "Africa-Canada Artificial Intelligence and Data Innovation Consortium" (ACADIC) Project in the Global South, and focusing on the ethical and regulatory challenges we had to face.…”

Section: Introductionmentioning

confidence: 99%

Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South

et al. 2023

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In the present paper, we will explore how artificial intelligence (AI) and big data analytics (BDA) can help address clinical public and global health needs in the Global South, leveraging and capitalizing on our experience with the “Africa-Canada Artificial Intelligence and Data Innovation Consortium” (ACADIC) Project in the Global South, and focusing on the ethical and regulatory challenges we had to face. “Clinical public health” can be defined as an interdisciplinary field, at the intersection of clinical medicine and public health, whilst “clinical global health” is the practice of clinical public health with a special focus on health issue management in resource-limited settings and contexts, including the Global South. As such, clinical public and global health represent vital approaches, instrumental in (i) applying a community/population perspective to clinical practice as well as a clinical lens to community/population health, (ii) identifying health needs both at the individual and community/population levels, (iii) systematically addressing the determinants of health, including the social and structural ones, (iv) reaching the goals of population’s health and well-being, especially of socially vulnerable, underserved communities, (v) better coordinating and integrating the delivery of healthcare provisions, (vi) strengthening health promotion, health protection, and health equity, and (vii) closing gender inequality and other (ethnic and socio-economic) disparities and gaps. Clinical public and global health are called to respond to the more pressing healthcare needs and challenges of our contemporary society, for which AI and BDA can help unlock new options and perspectives. In the aftermath of the still ongoing COVID-19 pandemic, the future trend of AI and BDA in the healthcare field will be devoted to building a more healthy, resilient society, able to face several challenges arising from globally networked hyper-risks, including ageing, multimorbidity, chronic disease accumulation, and climate change.

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Section: Introductionmentioning

confidence: 99%

Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South

et al. 2023

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Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South

Kong,

Akpudo,

Effoduh

et al. 2023

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<p>In the present paper, we will explore how artificial intelligence (AI) and big data analytics (BDA) can help address clinical public and global health needs in the Global South, leveraging and capitalizing on our experience with the “Africa-Canada Artificial Intelligence and Data Innovation Consortium” (ACADIC) Project in the Global South, and focusing on the ethical and regulatory challenges we had to face. “Clinical public health” can be defined as an interdisciplinary field, at the intersection of clinical medicine and public health, whilst “clinical global health” is the practice of clinical public health with a special focus on health issue management in resource-limited settings and contexts, including the Global South. As such, clinical public and global health represent vital approaches, instrumental in (i) applying a community/population perspective to clinical practice as well as a clinical lens to community/population health, (ii) identifying health needs both at the individual and community/population levels, (iii) systematically addressing the determinants of health, including the social and structural ones, (iv) reaching the goals of population’s health and well-being, especially of socially vulnerable, underserved communities, (v) better coordinating and integrating the delivery of healthcare provisions, (vi) strengthening health promotion, health protection, and health equity, and (vii) closing gender inequality and other (ethnic and socio-economic) disparities and gaps. Clinical public and global health are called to respond to the more pressing healthcare needs and challenges of our contemporary society, for which AI and BDA can help unlock new options and perspectives. In the aftermath of the still ongoing COVID-19 pandemic, the future trend of AI and BDA in the healthcare field will be devoted to building a more healthy, resilient society, able to face several challenges arising from globally networked hyper-risks, including ageing, multimorbidity, chronic disease accumulation, and climate change.</p>

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Principles to guide the effective use of technology to support capacity development in global health partnerships

Cited by 2 publications

References 35 publications

Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South

Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South

Leveraging Responsible, Explainable, and Local Artificial Intelligence Solutions for Clinical Public Health in the Global South

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