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Prediction of micronutrients deficiency among children under five in Nigeria using logistic regression approach

 Department: Computer Science  
 By: usericon MIke_Tech_World  

 Project ID: 8836
   Rating:  (5.0) votes: 1
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   Price:₦5000
Abstract
Micronutrient deficiencies are a major public health challenge in Nigeria in children under the age of five, and they have impacts on overall health, growth, and development. This study aims to predict such deficiencies using a machine learning technique, which in this case is the logistic regression relying on the following significant variables: dietary intake, maternal education, socioeconomic status, and other demographic variables. The data utilized in this study have some valuable characteristics, such as breastfeeding, eating patterns, and wealth of the family, which have been known to affect the levels of micronutrients in children. A high accuracy of 82% with high precision in the resulting logistic regression model showed that the model could be used to predict micronutrient deficiencies. Significant predictors of deficiencies were found in the study (diet and especially the intake of green leafy vegetables and meat, maternal education, and socioeconomic factors). A software program was designed to help ease the process of prediction and offer healthcare workers and caregivers a convenient tool to monitor the nutritional status of children....
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