A way to improve sustainable wellbeing using artificial intelligence techniques

Malnutrition is a global health issue that affects people of all ages especially children malnutrition can lead to various number of health problems. It is particularly prevalent in low income countries because of factors such as poverty, lack of nutrition food etc., This study aims to classify the malnutrition type, compute deficiency level and suggest suitable measure to patient through mobile app. To accomplish this Artificial Neural Network (ANN) is used to build this model. This study clarifies how predictive model classifies the malnutrition. ANN approach shows the best accuracy in predicting malnutrition deficiency. Global dataset is used to train the model. Pre-processing is done using imputation technique. Feature extraction is done with the help of CNN technique. Model building is done using ANN technique. Deficiency level of malnutrition is calculated with the help of benchmark values. Suitable measures for patients are suggest using mobile app.