AIMC Topic: Cardiopulmonary Resuscitation
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Comparison of Coopdech®, CoPilot®, Intubrite®, and Macintosh laryngoscopes for tracheal intubation during pediatric cardiopulmonary resuscitation: a randomized, controlled crossover simulation trial.
European journal of pediatrics
May 21, 2015
UNLABELLED: The aim of the study was to compare the intubation times and success rates of various laryngoscopes during resuscitation in pediatric emergency intubation with uninterrupted chest compression on a standardized pediatric manikin model. Thi...
Predicting shockable rhythms during chest compression with artificial intelligence: A winning bet?
Resuscitation
Sep 1, 2024
Reply to: "Predicting shockable rhythms during chest compression with artificial intelligence: A Winning Bet?".
Resuscitation
Sep 1, 2024
Artificial-intelligence-based neurological outcome prediction during out-of-hospital cardiac arrest.
Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias
Jun 1, 2024
Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study.
Medicine
May 31, 2024
This study aimed to evaluate the readability, reliability, and quality of responses by 4 selected artificial intelligence (AI)-based large language model (LLM) chatbots to questions related to cardiopulmonary resuscitation (CPR). This was a cross-sec...
Acceptability and Perceived Utility of Telemedical Consultation during Cardiac Arrest Resuscitation. A Multicenter Survey.
Annals of the American Thoracic Society
Mar 1, 2020
Many clinicians who participate in or lead in-hospital cardiac arrest (IHCA) resuscitations lack confidence for this task or worry about errors. Well-led IHCA resuscitation teams deliver better care, but expert resuscitation leaders are often unavai...
Convolutional Recurrent Neural Networks to Characterize the Circulation Component in the Thoracic Impedance during Out-of-Hospital Cardiac Arrest.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Pulse detection during out-of-hospital cardiac arrest remains challenging for both novel and expert rescuers because current methods are inaccurate and time-consuming. There is still a need to develop automatic methods for pulse detection, where the ...
A Robust Machine Learning Architecture for a Reliable ECG Rhythm Analysis during CPR.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2019
Chest compressions delivered during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG that may make the shock advice algorithms (SAA) of defibrillators inaccurate. There is evidence that methods consisting of adaptive filters that remov...
Predict In-Hospital Code Blue Events using Monitor Alarms through Deep Learning Approach.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
Bedside monitors in hospital intensive care units (ICUs) are known to produce excessive false alarms that could desensitize caregivers, resulting in delayed or even missed clinical interventions to life-threatening events. Our previous studies propos...
The effects of sternal intraosseous and intravenous administration of amiodarone in a hypovolemic swine cardiac arrest model.
American journal of disaster medicine
Jan 1, 2016
OBJECTIVE: This study compared the effects of amiodarone via sternal intraosseous (SIO) and intravenous (IV) routes on return of spontaneous circulation (ROSC), time to ROSC, concentration maximum (C), time to maximum concentration (T), and mean conc...
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