Predicting Child's Health using Big Data Analytics

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Vishal Johri
Varun Singh, Ishan Srivastava

Abstract

An era of open information in healthcare is now under way. We have already experienced a decade of progress in digitizing medical records, as pharmaceutical companies and other organizations aggregate years of research and development in electronic databases. Big Data analytics in healthcare deals with analysis of huge sets of electronic health records which are so complex that they cannot be maintained or analysed by traditional data processing applications. Big Data analytics in healthcare is useful in detecting diseases at early stage when they can be treated more efficiently, predicting outcomes of a surgery, etc. Mother's health during pregnancy and at the time of child's birth affects a range of health related factors in child, perhaps even in long-run. From the previous digital health data of mothers at the time of delivery and health issues in their babies, analysis can be done and prediction model can be created. This model will assist in taking appropriate precautions and treating diseases at early stages which will improve overall health of babies. This paper is structured as follows- first we have listed few health issues in pregnant women which affect their children. Then, we have proposed a model which can help in improving child's health. In the end we will elaborate advantages and challenges faced by the proposed model.

 

Keywords: Big Data Analytics; healthcare; mother; child; electronic health records; proposed model

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