Real Time Child Infant Mortality Analysis for Efficient Public Health Development

Abstract

The problem of child health management and development has been well studied. There are number of methods available for the problem of child health development but suffers to achieve higher performance. To improve the performance, an efficient real time child infant mortality analysis for improved health development using multi feature covariance measure (MFCM). The method maintains number of data records of various child and infants from the age of 1 month to 15 years. For each child or infant, the method maintains continuous records of their health diagnosis. Using the data maintained, the method identifies and groups them according to the cause of death. Using the cluster generated, the method estimates health factor influence (HFI) for different features. Based on the value of HFI, a set of features which has higher HFI are selected and used to generate analysis. Further the method generates a prediction result on the future mortality and the reasons. The method improves the performance of mortality prediction and increases the accuracy also.