Artificial intelligence approach for analyzing anaemia prevalence in children and adolescents in Brics countries: a review
SOURCE: Current Research in Nutrition and Food Science
OUTPUT TYPE: Journal Article
PUBLICATION YEAR: 2021
TITLE AUTHOR(S): N.Dukhi, R.Sewpaul, M.D.Sekgala, O.O.Awe
KEYWORDS: ADOLESCENTS, ARTIFICIAL INTELLIGENCE (AI), BRAZIL-RUSSIA-INDIA-CHINA-SOUTH AFRICA (BRICS), CHILDREN, SICKLE CELL ANEMIA
DEPARTMENT: Public Health, Societies and Belonging (HSC)
Print: HSRC Library: shelf number 11939
HANDLE: 20.500.11910/15947
URI: http://hdl.handle.net/20.500.11910/15947
OUTPUT TYPE: Journal Article
PUBLICATION YEAR: 2021
TITLE AUTHOR(S): N.Dukhi, R.Sewpaul, M.D.Sekgala, O.O.Awe
KEYWORDS: ADOLESCENTS, ARTIFICIAL INTELLIGENCE (AI), BRAZIL-RUSSIA-INDIA-CHINA-SOUTH AFRICA (BRICS), CHILDREN, SICKLE CELL ANEMIA
DEPARTMENT: Public Health, Societies and Belonging (HSC)
Print: HSRC Library: shelf number 11939
HANDLE: 20.500.11910/15947
URI: http://hdl.handle.net/20.500.11910/15947
If you would like to obtain a copy of this Research Output, please contact Hanlie Baudin at researchoutputs@hsrc.ac.za.
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.-
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