Artificial Intelligence Approach for Analyzing Anaemia Prevalence in Children and Adolescents in BRICS Countries: A Review

Author:

Dukhi Natisha1ORCID,Sewpaul Ronel1ORCID,Derrick Sekgala Machoene1ORCID,Olawale Awe Olushina2ORCID

Affiliation:

1. 1Human and Social Capabilities Division, Human Sciences Research Council, Merchant House, 116-118 Buitengracht Street, Cape Town, South Africa.

2. 2Department of Mathematical Sciences, Anchor University Lagos, Lagos, Nigeria. 3Institute of Mathematics and Statistics, Federal University of Bahia (UFBA), Salvador, Brazil.

Abstract

Anemia prevalence, especially among children and adolescents, is a serious public health burden in the BRICS countries. This article gives an overview of the current anaemia status in children and adolescents in three BRICS countries, as part of a study that utilizes an artificial intelligence approach for analyzing anaemia prevalence in children and adolescents in South Africa, India and Russia. It posits that the use of machine learning in this area of health research is still novel. The weightage assessment of the crosslink between anaemia risk indicators using a machine learning approach will assist policy makers in identifying the areas of priority to intervene in the BRICS participating countries. Health interventions utilizing artificial intelligence and more specifically, machine learning techniques, remains nascent in LMICs but could lead to improved health outcomes.

Funder

National Research Foundation

Publisher

Enviro Research Publishers

Subject

Medicine (miscellaneous),Food Science

Reference51 articles.

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