A Systematic Review of the Use of Conversational Artificial Intelligence for Improving Patient Diagnostics and Engagement in Sub-Saharan Africa

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dc.contributor.authorIloekwe J.O.
dc.date.accessioned2024-11-26T08:30:05Z
dc.date.available2024-11-26T08:30:05Z
dc.date.issued2024-11-25
dc.descriptionScholarly article
dc.description.abstractConversational Artificial Intelligence (AI) has emerged as a transforming medical tool, specifically in marginalized parts of the continent such as sub-Saharan Africa. This paper is an exploration of conversational AI’s implementation in healthcare, with a focus on its capacity to improve patient engagement and diagnostics. Babylon Health in Rwanda and mTIBA in Kenya are case studies utilized by the paper to show diverse ways AI-based platforms have been applied to increase healthcare accessibility, specifically in marginalized communities. There is a lot of potential for the implementation of conversational AI in medicine within sub-Saharan Africa. Nonetheless, a few drawbacks, including issues of data privacy, scarcity of digital architecture and cultural diversity exist. To efficiently scale and adopt the application of this AI system in the region, these barriers must be overcome. The paper concludes with an outline of growth opportunities and future applications of conversational AI in sub-Saharan Africa’s medical landscape.
dc.identifier.citationIloekwe J.O. (2024). “A Systematic Review of the Use of Conversational Artificial Intelligence for Improving Patient Diagnostics and Engagement in Sub-Saharan Africa ". In Proceedings of the International Conference on Artificial Intelligence and Robotics (MIRG-ICAIR 2024), pp. 97-105, MIRG
dc.identifier.isbn978-978-771-680-9
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/13053
dc.language.isoen
dc.publisherMIRG
dc.relation.ispartofseriesMIRG-ICAIR 2024
dc.titleA Systematic Review of the Use of Conversational Artificial Intelligence for Improving Patient Diagnostics and Engagement in Sub-Saharan Africa
dc.typeArticle
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