A survey on prediction of anemia in pregnant women based on NFHS-4 dataset using ML approaches.

Anemia disease is a common health problem in emerging countries and constitutes a challenge to public health in India as well. It affects persons of all age groups, especially women and children. India has the maximum total prevalence of anemia at 39.86%. According to WHO, about 32.4 million pregnant women suffer from anemia disease. The NFHS-4 provides crucial date related to anemic status in India. The prevalence percentage of anemia in pregnant women in India using the NFHS-4 survey remained 50.2%. Machine learning algorithms and data mining techniques open new doors of opportunities for precise prediction of Anemia disease. Still, the resourceful processing of such huge data is exciting, so we need a system that infers from the data. ML methods make systems learn itself. In this paper, we have presented a survey of ML algorithms used for prediction of anemia in pregnant women from NFHS-4. [ABSTRACT FROM AUTHOR]