Severe or life threatening infections are common among patients in the intensive care unit
(ICU). Most infections in the ICU are bacterial or fungal in origin and require antimicrobial …

Early recognition and treatment of sepsis are linked to improved patient outcomes. Machine
learning-based early warning systems may reduce the time to recognition, but few systems …

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 …

Abstract Machine learning-based clinical decision support tools for sepsis create
opportunities to identify at-risk patients and initiate treatments at early time points, which is …

Objectives: To provide contemporary estimates of the burdens (costs and mortality)
associated with acute inpatient Medicare beneficiary admissions for sepsis. Design …

Background Timely interventions, such as antibiotics and intravenous fluids, have been
associated with reduced mortality in patients with sepsis. Artificial intelligence (AI) models …

Sepsis is a complex and heterogeneous syndrome that remains a serious challenge to
healthcare worldwide. Patients afflicted by severe sepsis or septic shock are customarily …

Acute mesenteric ischemia (AMI) is a severe condition associated with poor prognosis,
ultimately leading to death due to multiorgan failure. Several mechanisms may lead to AMI …

Sepsis is a major cause of death worldwide. Over the past years, prediction of clinically
relevant events through machine learning models has gained particular attention. In the …

Sepsis is a life-threatening condition caused by an exaggerated reaction of the body to an
infection, that leads to organ failure or even death. Since sepsis can kill a patient even in just …