Data revolution, health status transformation and the role of artificial intelligence for health and pandemic preparedness in the African context.

Q2 Biochemistry, Genetics and Molecular Biology BMC Proceedings Pub Date : 2021-11-22 DOI:10.1186/s12919-021-00228-1
Sunny Ibeneme, Joseph Okeibunor, Derrick Muneene, Ishrat Husain, Pascoal Bento, Carol Gaju, Ba Housseynou, Moredreck Chibi, Humphrey Karamagi, Lindiwe Makubalo
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引用次数: 6

Abstract

Background: Artificial Intelligence (AI) platforms, increasingly deployed in public health, utilize robust data systems as a critical component for health emergency preparedness. Yet, Africa faces numerous challenges in the availability, analyses, and use of data to inform health decision-making. Countries have limited access to their population data. Those with access, struggle to utilize these data for program improvements. Owing to the rapid growth of mobile phone ownership and use in the region, Africa is poised to leverage AI technologies to increase the adoption, access and use of data for health. To discuss and propose solutions for responsible development and adoption of innovations like AI in Africa, a virtual workshop was organized from the 21st to 24th June, 2021. This report highlights critical policy dimensions of strengthening digital health ecosystems by high-level policymakers, technical experts, academia, public and private sector partners.

Method: The four days' workshop focused on nine sessions, with each session focusing on three themes. Discussions during the sessions concentrated on public and private sectors, the academia and multilateral organizations' deployment of AI. These discussions expanded participants' understanding of AI, the opportunities and challenges that exist during adoption, including the future of AI for health in the African region. Approximately 250 participants attended the workshop, including countries representatives from ministries of Health, Information and Technology, Developmental Organizations, Private Sector, Academia and Research Institutions among others.

Results: The workshop resolved that governments and relevant stakeholders should collaborate to ensure that AI and digital health receive critical attention. Government ownership and leadership were identified as critical for sustainable financing and effective scale-up of AI-enabled applications in Africa. Thus, government is to ensure that key recommendations from the workshop are implemented to improve health sector development in Africa.

Conclusions: The AI workshop was a good forum to deliberate important issues regarding AI for health in the African context. It was concluded that there is a need to focus on vital priorities in deploying AI in Africa: Data protection, privacy and sharing protocols; training and creating platforms for researchers; funding and business models; developing frameworks for assessing and implementing AI; organizing forums and conferences on AI; and instituting regulations, governance and ethical guidelines for AI. There is a need to adopt a health systems approach in planning for AI to reduce inefficiencies, redundancies while increasing effectiveness in the use of AI. Thus, robust collaborations and partnerships among governments and various stakeholders were identified as key.

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数据革命、卫生状况转变以及人工智能在非洲卫生和大流行病防范方面的作用。
背景:越来越多地在公共卫生领域部署的人工智能(AI)平台利用强大的数据系统作为卫生应急准备的关键组成部分。然而,非洲在提供、分析和使用数据为卫生决策提供信息方面面临许多挑战。各国获取人口数据的途径有限。那些有访问权限的人,努力利用这些数据来改进程序。由于该区域移动电话拥有量和使用量的迅速增长,非洲已准备好利用人工智能技术来增加卫生数据的采用、获取和使用。为了讨论和提出解决方案,促进非洲负责任的发展和采用人工智能等创新,于2021年6月21日至24日组织了一次虚拟研讨会。本报告强调了高层决策者、技术专家、学术界、公共和私营部门合作伙伴加强数字卫生生态系统的关键政策层面。方法:为期四天的研讨会分为九个环节,每个环节分别围绕三个主题展开。会议期间的讨论集中在公共和私营部门、学术界和多边组织对人工智能的部署。这些讨论扩大了与会者对人工智能、采用过程中存在的机遇和挑战的理解,包括人工智能促进非洲区域卫生的未来。大约250名与会者参加了讲习班,其中包括来自卫生部、信息和技术部、发展组织、私营部门、学术界和研究机构等的国家代表。结果:研讨会决定,各国政府和相关利益攸关方应开展合作,确保人工智能和数字卫生得到高度重视。与会者认为,政府的所有权和领导对非洲可持续融资和有效扩大人工智能应用至关重要。因此,政府应确保讲习班提出的关键建议得到执行,以改善非洲卫生部门的发展。结论:人工智能讲习班是讨论非洲卫生领域人工智能重要问题的良好论坛。会议的结论是,在非洲部署人工智能时,有必要把重点放在至关重要的优先事项上:数据保护、隐私和共享协议;为研究人员提供培训和创建平台;资金和商业模式;制定评估和实施人工智能的框架;组织有关人工智能的论坛和会议;为人工智能制定法规、治理和道德准则。有必要在规划人工智能时采用卫生系统方法,以减少低效率和冗余现象,同时提高人工智能使用的有效性。因此,政府和各利益攸关方之间强有力的合作和伙伴关系被确定为关键。
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来源期刊
BMC Proceedings
BMC Proceedings Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
3.50
自引率
0.00%
发文量
6
审稿时长
10 weeks
期刊最新文献
Harnessing the power of artificial intelligence for disease-surveillance purposes. Effective communication during disease outbreaks: the role of data journalism in pandemic and epidemic intelligence. Abstracts from the 13th International Conference for Healthcare and Medical Students (ICHAMS). Pandemic and epidemic intelligence innovation forum: bridging gaps in epidemic intelligence through global collaboration. Pathways to strengthening the epidemic intelligence workforce.
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