AIMC Topic: Cardiopulmonary Resuscitation

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A Machine Learning Shock Decision Algorithm for Use During Piston-Driven Chest Compressions.

IEEE transactions on bio-medical engineering
GOAL: Accurate shock decision methods during piston-driven cardiopulmonary resuscitation (CPR) would contribute to improve therapy and increase cardiac arrest survival rates. The best current methods are computationally demanding, and their accuracy ...

Newborn self-inflating manual resuscitators: precision robotic testing of safety and reliability.

Archives of disease in childhood. Fetal and neonatal edition
AIM: A controlled bench test was undertaken to determine the performance variability among a range of neonatal self-inflating bags (SIB) compliant with current International Standards Organisation (ISO).

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
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...

Assessing the readability, reliability, and quality of artificial intelligence chatbot responses to the 100 most searched queries about cardiopulmonary resuscitation: An observational study.

Medicine
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
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
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 ...