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Published in:
2020 | OriginalPaper | Chapter
A Threat Towards the Neonatal Mortality
Authors : Kumari Deepika, Santosh Chowhan
Published in: Advances in Computing and Data Sciences
Publisher: Springer Singapore
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Abstract
This paper focusses on review and an analysis of the observational studies or case control studies for identification of the threats to the neonatal stage as it is the critical phase for the adaption of the extrauterine life so that significant risk factors are deduced and aiming at the reduction in the mortality of neonatal. Vulnerabilities with respect to both maternal as well as neonatal threatened the survival of neonates. These threats impact economically, socially, psychologically and physical. Predictive analytics to be done through the techniques of machine learning. Supervised learning techniques are adopted for analysis of threats to the neonatal stage. This process splits in two sets: from a give data set, unknown dependencies are to be estimated for training the model and outputs of the system is to be predicted or tested by using estimated dependencies. In future, model can be designed to predict the threats and diseases.