Infant Birth Weight Estimation Using Machine Learning

Recent studies show that at least 7 out of 100 babies born in 2015 were under the recommended birth weight of 2.5 kg according to UNICEF. There are various factors that influence low birth weight including baby's sex, age of mother and father, living conditions, smoking and drinking habits, weight gained during pregnancy, etc. According to doctors, the decline in the average birth weight is a warning sign of the dangers of undernourishment, juvenile illnesses, and even mortality. The idea of the project is to help mothers estimate the baby's birth weight using various machine learning algorithms and determine which algorithm is best suited for this research study. The proposed model can recommend appropriate meal programs to simultaneously improve the health of the mother and infant based on the estimation that the algorithm provides so this study will help to monitor the low birth weight of infants and also the mother's health.