IEEE journal of biomedical and health informatics
Feb 10, 2020
Medicine has entered the digital era, driven by data from new modalities, especially genomics and imaging, as well as new sources such as wearables and Internet of Things. As we gain a deeper understanding of the disease biology and how diseases affe...
In order to evaluate mortality predictions based on boosted trees, this retrospective study uses electronic medical record data from three academic health centers for inpatients 18 years or older with at least one observation of each vital sign. Pred...
Journal of infection in developing countries
Nov 30, 2019
INTRODUCTION: Sepsis represents a major cause of morbidity and mortality in critically ill patients. Early diagnosis and appropriate treatment have a crucial influence on survival. The aim of this study was to evaluate the diagnostic and prognostic r...
OBJECTIVE: Achieving accurate prediction of sepsis detection moment based on bedside monitor data in the intensive care unit (ICU). A good clinical outcome is more probable when onset is suspected and treated on time, thus early insight of sepsis ons...
BACKGROUND: We hypothesized utilizing machine learning (ML) algorithms for screening septic shock in ED would provide better accuracy than qSOFA or MEWS.
Many studies have been published on a variety of clinical applications of artificial intelligence (AI) for sepsis, while there is no overview of the literature. The aim of this review is to give an overview of the literature and thereby identify know...
Sepsis is the leading cause of death in non-coronary intensive care units. Moreover, a delay of antibiotic treatment of patients with severe sepsis by only few hours is associated with increased mortality. This insight makes accurate models for early...
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
Sep 17, 2019
BACKGROUND: Machine learning (ML) is a growing field in medicine. This narrative review describes the current body of literature on ML for clinical decision support in infectious diseases (ID).