Motivation and objective: Emergency medicine is becoming a popular application area for
artificial intelligence methods but remains less investigated than other healthcare branches …

Our scoping review provides a comprehensive analysis of the landscape of artificial
intelligence (AI) applications in prehospital emergency care (PEC). It contributes to the field …

High performance of the shock advisory analysis of the electrocardiogram (ECG) during
cardiopulmonary resuscitation (CPR) in out-of-hospital cardiac arrest (OHCA) is important …

Background Because chest compressions induce artifacts in the ECG, current automated
external defibrillators instruct the user to stop cardiopulmonary resuscitation (CPR) while an …

Chest compressions during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG
that may provoque inaccurate rhythm classification by the algorithm of the defibrillator. The …

Goal: Identifying the circulation state during out-of-hospital cardiac arrest (OHCA) is
essential to determine what life-saving therapies to apply. Currently algorithms discriminate …

This study aims to present a novel deep learning algorithm for a sliding shock advisory
decision during cardiopulmonary resuscitation (CPR) and its performance evaluation as a …

Feedback on ventilation could help improve cardiopulmonary resuscitation quality and
survival from out-of-hospital cardiac arrest (OHCA). However, current technology that …

Aim of the study This study aimed to develop an artificial intelligence (AI) model capable of
predicting shockable rhythms from electrocardiograms (ECGs) with compression artifacts …

Pulseless electrical activity (PEA) is characterized by the disassociation of the mechanical
and electrical activity of the heart and appears as the initial rhythm in 20–30% of out-of …