Artificial intelligence approach for analyzing anaemia prevalence in children and adolescents in Brics countries: a review

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.

Publication Details

Journal
Human Science Research Council SA
Published
2025-12-09
DOI
https://doi.org/10.14749/30828170
Primary Topic
Iron Metabolism and Disorders
Type
article
Field-Weighted Citation Impact
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article

Artificial intelligence approach for analyzing anaemia prevalence in children and adolescents in Brics countries: a review

Human Science Research Council SA
Iron Metabolism and Disorders
article

Artificial intelligence approach for analyzing anaemia prevalence in children and adolescents in Brics countries: a review

article en

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.

Human Science Research Council SA
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Iron Metabolism and Disorders
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