Machine Learning based Factors affecting Malnutrition and Anemia among children in India

Malnutrition and Anemia are some of the prime causes of infant mortality among various developing countries such as India. This study aims to identify the most important features available in the Indian Demographic and Health Survey (IDHS) dataset and design a prognostic model for diagnosing malnutrition using these key features. Demographic and Health Checks (DHS) are conducted every 5 years nationwide, supplying data for an extensive range of tracking, monitoring, and evaluating pointers in the areas of nutrition, health, and population. This project employs the machine learning approach to identify the various features influencing malnutrition and have correlated its association to anemia, which has not been linked to existent literature yet. Moreover, the degree to which these features influence malnutrition are identified, and location-specific features for the children living in various Indian states are targeted.