Sepsis is one of the main causes of death in critically ill patients. Despite the continuous
development of medical technology in recent years, its morbidity and mortality are still high …

Objectives This systematic review aimed to assess the performance and clinical feasibility of
machine learning (ML) algorithms in prediction of in-hospital mortality for medical patients …

Abstract Deep Reinforcement Learning (DRL) has been increasingly attempted in assisting
clinicians for real-time treatment of sepsis. While a value function quantifies the performance …

Abstract Background and Objective: Generative adversarial network (GAN) is able to learn
from a set of training data and generate new data with the same characteristics as the …

Background and objectives Sepsis is accompanied by a considerably high risk of mortality in
the short term, despite the availability of recommended mortality risk assessment tools …

Background Sepsis is a life-threatening condition caused by an abnormal response of the
body to infection and imposes a significant health and economic burden worldwide due to its …

Background Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in
patients with sepsis can be predicted early, medical resources can be allocated efficiently …

As global demographics change, ageing is a global phenomenon which is increasingly of
interest in our modern and rapidly changing society. Thus, the application of proper …

The early diagnosis of sepsis reduces the risk of the patient's death. Gradient-based
algorithms are applied to the neural network models used in the estimation of sepsis in the …

Sepsis is an inflammation caused by the body's systemic response to an infection. The
infection could be a result of many diseases, such as pneumonia, urinary tract infection, and …