Current Research in Nutrition and Food Science - An open access, peer reviewed international journal covering all aspects of Nutrition and Food Science

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

Natisha Dukhi¹*, Ronel Sewpaul¹, Machoene Derrick Sekgala¹ and Olushina Olawale Awe^2,3

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

²Department of Mathematical Sciences, Anchor University Lagos, Lagos, Nigeria.

³Institute of Mathematics and Statistics, Federal University of Bahia (UFBA), Salvador, Brazil.

Corresponding Author Email: doctordukhi@gmail.com

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.

Keywords:

Adolescents; Anaemia; BRICS; Children; Machine Learning

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