Background The design of computerized systems able to support automated detection of
threatening conditions in critically ill patients such as systemic inflammatory response …

Background Prediction modelling can greatly assist the health-care professionals in the
management of diseases, thus sparking interest in neonatal sepsis diagnosis. The main …

Sepsis and Neonatal sepsis are major challenges in global healthcare because they cause
life-threatening organ dysfunction in intensive care adult and pediatric patients due to down …

About 2.9 million neonates die every year worldwide, and most of these deaths occur in low-
resource settings. Neonatal sepsis occurs when there is a bacterial invasion in the …

This Sepsis, commonly called as 'blood poisoning', is really the adverse consequence of the
body's response to an infection, which results in organ damage. It is recognized as a global …

This paper aims at presenting a method and comparing various machine learning (ML) and
deep learning (DL) algorithms for predicting sepsis from clinical time-series data. Sepsis is …

In 2016, approximately 6 million children died worldwide. A total of 1 million of these
children died within the first 24 h of their birth. Majority of these deaths are due to infectious …

This thesis systematically reviewed the relevant literature, summarised the current research
status in computer-aided sepsis detection, and proposed a unified sepsis detection …