Experimentation of AI Models Towards the Prediction of Medium-Risk Emergency Department Cases Disposition Outcome.

The overwhelming volume of patients in emergency departments (EDs) is a significant problem that hinders the delivery of high quality healthcare. Despite their great value, triage protocols are challenging to put into practice. This paper examines the utility of prediction models as a tool for clinical decision support, with a focus on medium-severity patients as defined by the ESI algorithm.

Towards the Definition of an Intelligent Triage and Continuous Monitoring System for Hospital Emergency Departments and Clinics.

Recent statistics have demonstrated that Emergency Departments (EDs) in Greece lack in organization and service. In most cases, patient prioritization is not automatically implemented. The main objective of this paper is to present IntelTriage, a smart triage system, that dynamically assigns priorities to patients in an ED and monitors their vital signs and location during their stay in the clinic through wearable biosensors.

Correlation of central venous-arterial and mixed venous-arterial carbon dioxide tension gradient with cardiac output during neurosurgical procedures in the sitting position.

Background And Objective: The study was conducted to evaluate the correlation of central venous-arterial and mixed venous-arterial pCO(2) gradient with cardiac output in patients being operated in the sitting position.

Methods: Fifty-one patients, aged 41-69 years, classified as American Society of Anesthesiologists physical status II and III, scheduled to undergo elective neurosurgical procedures in the sitting position, were enrolled in this prospective cohort study. Simultaneous blood gas samples from arterial, central venous and pulmonary artery catheters were collected at four different time points during supine and sitting position.