Risk Factors Identification and Prediction of Anemia among Women in Bangladesh using Machine Learning Techniques

Background: Anemia is a major public health problem with raising prevalence worldwide, including Bangladesh. Objectives: To identify the risk factors of anemia among women in Bangladesh and its prediction using Machine Learning (ML) based techniques. Methods: The anemia dataset, comprising of 3,020 respondents, was extracted from the Bangladesh Demographic and Health Survey (BDHS). Two feature selection techniques as Logistic Regression (LR) and Random Forest (RF), have been utilized to determine the risk factors of anemia. Additionally, eight ML-based techniques, namely LR, Linear Discriminant Analysis (LDA), K-Nearest Neighborhood (KNN), Support Vector Machine (SVM), Quadratic Discriminant Analysis (QDA), Neural Network (NN), Classification And Regression Tree (CART), and RF have also been utilized to predict anemia disease among women in Bangladesh. Classification accuracy…