Background Artificial intelligence (AI) holds significant potential to be a valuable tool in
healthcare. However, its application for predicting bacteremia among adult febrile patients in …

Introduction In the past few years, the use of artificial intelligence in healthcare has grown
exponentially. Prescription of antibiotics is not exempt from its rapid diffusion, and various …

Abstract Background Bloodstream infections (BSIs) are a significant burden on the global
population and represent a key area of focus in the hospital environment. Blood culture (BC) …

The protective effects of commensal, anaerobic, gut microbiota have been established in
various acute diseases [1–3]. This raises the question whether antibiotics depleting these …

Background Excessive use of blood cultures (BCs) in Emergency Departments (EDs) results
in low yields and high contamination rates, associated with increased antibiotic use and …

Background: A correct approach to recurrent urinary tract infections (rUTIs) is an important
pillar of antimicrobial stewardship. We aim to define an Artificial Neural Network (ANN) for …

Objective Sepsis is a life-threatening condition in the ICU and requires treatment in time.
Despite the accuracy of existing sepsis prediction models, insufficient focus on reducing …

Background Bacteremia is a life-threatening complication of infectious diseases. Bacteremia
can be predicted using machine learning (ML) models, but these models have not utilized …

Introduction. The term 'diagnostic stewardship'is relatively new, with a recent surge in its use
within the literature. Despite its increasing popularity, a precise definition remains elusive …

Rationale: Despite the importance of sepsis surveillance, no optimal approach for identifying
sepsis hospitalizations exists. The Centers for Disease Control and Prevention Adult Sepsis …