Autors: Muchapa P.T., Kasereka S.K., Pinto J.K., Mandiya R.E., Mulomba C.M., Ngoie R.B.M., Slavov, V. D., Tashev, T. A., Kyamakya K.
Title: Enhancing Healthcare in Africa using Statistical Learning: Applications and Opportunities
Keywords: Africa, Artificial intelligence, Decision-making, Disease prediction, Epidemiology, Healthcare, Statistical learning

Abstract: Published by Elsevier B.V.This review examines its role in African healthcare and its application in advancing medical imaging, epidemiological surveillance, and resource management. A review of 40 recent studies highlights key challenges, including data scarcity, inequity, inadequate infrastructure, and a shortage of qualified professionals, which hinder the large-scale implementation of these technologies. For responsible and effective integration, we suggest addressing several considerations - legal, ethical, and governance - beyond technical barriers. Although focused on Africa, this review incorporates studies from non-African countries to enrich the analysis and identify transferable strategies, given the limited number of African publications in the field. It proposes innovative pathways tailored to the continent's healthcare systems.

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Issue

Procedia Computer Science, vol. 265, pp. 268-275, 2025, Albania, https://doi.org/10.1016/j.procs.2025.07.181

Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus