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Out-of-Hospital Cardiac Arrest

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Mixed convolutional and long short-term memory network for the detection of lethal ventricular arrhythmia.

PloS one 31107876
Early defibrillation by an automated external defibrillator (AED) is key for the survival of out-of-hospital cardiac arrest (OHCA) patients. ECG feature extraction and machine learning have been successfully used to detect ventricular fibrillation (V...
Algorithms Databases, Factual Deep Learning Defibrillators Diagnosis, Computer-Assisted Electric Countershock Electrocardiography Electrocardiography, Ambulatory Humans Neural Networks, Computer Out-of-Hospital Cardiac Arrest Signal Processing, Computer-Assisted Support Vector Machine Ventricular Fibrillation
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Outcome prediction of out-of-hospital cardiac arrest with presumed cardiac aetiology using an advanced machine learning technique.

Resuscitation 31220514
BACKGROUND: Outcome prediction for patients with out-of-hospital cardiac arrest (OHCA) has the possibility to detect patients who could have been potentially saved. Advanced machine learning techniques have recently been developed and employed for cl...
Adolescent Adult Cohort Studies Humans Machine Learning Models, Theoretical Out-of-Hospital Cardiac Arrest Prognosis Survival Rate
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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 31946274
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 ...
Cardiopulmonary Resuscitation Electric Impedance Humans Neural Networks, Computer Out-of-Hospital Cardiac Arrest Pulse
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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 31946270
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...
Algorithms Artifacts Cardiopulmonary Resuscitation Defibrillators Electrocardiography Humans Machine Learning Out-of-Hospital Cardiac Arrest Sensitivity and Specificity
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Prediction of good neurological recovery after out-of-hospital cardiac arrest: A machine learning analysis.

Resuscitation 31362082
BACKGROUND: This study aimed to train, validate and compare predictive models that use machine learning analysis for good neurological recovery in OHCA patients.
Cardiopulmonary Resuscitation Clinical Decision Rules Heart Diseases Humans Machine Learning Nervous System Diseases Out-of-Hospital Cardiac Arrest Prognosis Recovery of Function Reproducibility of Results
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Identifying the relative importance of predictors of survival in out of hospital cardiac arrest: a machine learning study.

Scandinavian journal of trauma, resuscitation and emergency medicine 32586339
INTRODUCTION: Studies examining the factors linked to survival after out of hospital cardiac arrest (OHCA) have either aimed to describe the characteristics and outcomes of OHCA in different parts of the world, or focused on certain factors and wheth...
Age Factors Aged Algorithms Cardiopulmonary Resuscitation Emergency Medical Services Female Heart Rate Humans Machine Learning Male Out-of-Hospital Cardiac Arrest Survival Analysis Sweden Time-to-Treatment
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Artificial neural networks improve early outcome prediction and risk classification in out-of-hospital cardiac arrest patients admitted to intensive care.

Critical care (London, England) 32731878
BACKGROUND: Pre-hospital circumstances, cardiac arrest characteristics, comorbidities and clinical status on admission are strongly associated with outcome after out-of-hospital cardiac arrest (OHCA). Early prediction of outcome may inform prognosis,...
Aged Critical Care Female Hospitalization Humans Hypothermia, Induced Male Middle Aged Neural Networks, Computer Out-of-Hospital Cardiac Arrest Prognosis Reproducibility of Results Risk Assessment ROC Curve
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Effect of Machine Learning on Dispatcher Recognition of Out-of-Hospital Cardiac Arrest During Calls to Emergency Medical Services: A Randomized Clinical Trial.

JAMA network open 33404620
IMPORTANCE: Emergency medical dispatchers fail to identify approximately 25% of cases of out-of-hospital cardiac arrest (OHCA), resulting in lost opportunities to save lives by initiating cardiopulmonary resuscitation.
Aged Denmark Double-Blind Method Emergency Medical Dispatch Female Humans Machine Learning Male Out-of-Hospital Cardiac Arrest
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Predicting neurological outcome after out-of-hospital cardiac arrest with cumulative information; development and internal validation of an artificial neural network algorithm.

Critical care (London, England) 33632280
BACKGROUND: Prognostication of neurological outcome in patients who remain comatose after cardiac arrest resuscitation is complex. Clinical variables, as well as biomarkers of brain injury, cardiac injury, and systemic inflammation, all yield some pr...
Adult Aged Area Under Curve Biomarkers Female Humans Male Middle Aged Neural Networks, Computer Out-of-Hospital Cardiac Arrest Prognosis Prospective Studies Retrospective Studies Risk Assessment ROC Curve
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Deep Neural Network Approach for Continuous ECG-Based Automated External Defibrillator Shock Advisory System During Cardiopulmonary Resuscitation.

Journal of the American Heart Association 33663222
Background Because chest compressions induce artifacts in the ECG, current automated external defibrillators instruct the user to stop cardiopulmonary resuscitation (CPR) while an automated rhythm analysis is performed. It has been shown that minimiz...
Algorithms Artifacts Cardiopulmonary Resuscitation Deep Learning Defibrillators Electrocardiography Humans Neural Networks, Computer Out-of-Hospital Cardiac Arrest
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