Clinical Indicator Analysis for Predicting Pathogenic Pneumonia Infection in Newborns with Distributed Sensor Networks Data Analytics

Abstract

Neonatal infections are prevalent as newborn children are prone to a range of infections because of their absence of immunity. Being susceptible to various diseases, the immune system of infants is not adequately developed to fight against protozoa bacteria, viruses and parasites. Pathogenic pneumonia is one of the most common infections identified within the neonatal group. It is a lung infection occurring in the neonates, which can start after a few hours of delivery or even after a week. The infection can even occur due to the normal flora found in the genital tract of the mother, and the respiratory distress caused by pathogenic pneumonia can even lead to the infant's death. The study examined the clinical indicator for assessing the occurrence of pathogenic pneumonia in infants. With the help of sensor networking in data analytics, the prediction of such a disorder has been assessed in-depth in the article.