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Now showing items 1-10 of 18
Towards the Prediction of Rearrest during Out-of-Hospital Cardiac Arrest
(MDPI, 2020-07-09)
A secondary arrest is frequent in patients that recover spontaneous circulation after an out-of-hospital cardiac arrest (OHCA). Rearrest events are associated to worse patient outcomes, but little is known on the heart ...
Fuzzy and Sample Entropies as Predictors of Patient Survival Using Short Ventricular Fibrillation Recordings during out of Hospital Cardiac Arrest
(MDPI, 2018-08)
Optimal defibrillation timing guided by ventricular fibrillation (VF) waveform analysis would contribute to improved survival of out-of-hospital cardiac arrest (OHCA) patients by minimizing myocardial damage caused by ...
Application of entropy-based features to predict defibrillation outcome in cardiac arrest
(MDPI, 2016-08)
Prediction of defibrillation success is of vital importance to guide therapy and improve the survival of patients suffering out-of-hospital cardiac arrest (OHCA). Currently, the most efficient methods to predict shock ...
A New Method for Feedback on the Quality of Chest Compressions during Cardiopulmonary Resuscitation
(Hindawi Publishing, 2014)
Quality of cardiopulmonary resuscitation (CPR) improves through the use of CPR feedback devices. Most feedback devices integrate the acceleration twice to estimate compression depth. However, they use additional sensors ...
A Reliable Method for Rhythm Analysis during Cardiopulmonary Resuscitation
(Hindawi Publishing, 2014)
nterruptions in cardiopulmonary resuscitation (CPR) compromise defibrillation success. However, CPR must be interrupted to analyze the rhythm because although current methods for rhythm analysis during CPR have high ...
Analysis of Few-Shot Techniques for Fungal Plant Disease Classification and Evaluation of Clustering Capabilities Over Real Datasets
(Frontiers Media, 2022-03)
[EN] Plant fungal diseases are one of the most important causes of crop yield losses. Therefore, plant disease identification algorithms have been seen as a useful tool to detect them at early stages to mitigate their ...
Rhythm Analysis during Cardiopulmonary Resuscitation: Past, Present, and Future
(Hindawi, 2014-01)
Survival from out-of-hospital cardiac arrest depends largely on two factors: early cardiopulmonary resuscitation (CPR) and early defibrillation. CPR must be interrupted for a reliable automated rhythm analysis because chest ...
Machine Learning Techniques for the Detection of Shockable Rhythms in Automated External Defibrillators
(Public Library Science, 2016-07-21)
Early recognition of ventricular fibrillation (VF) and electrical therapy are key for the survival of out-of-hospital cardiac arrest (OHCA) patients treated with automated external defibrillators (AED). AED algorithms for ...
A Machine Learning Model for the Prognosis of Pulseless Electrical Activity during Out-of-Hospital Cardiac Arrest
(MDPI, 2021-06-30)
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-hospital cardiac arrest (OHCA) cases. ...
Rhythm Analysis during Cardiopulmonary Resuscitation Using Convolutional Neural Networks
(MDPI, 2020-05-27)
Chest compressions during cardiopulmonary resuscitation (CPR) induce artifacts in the ECG that may provoque inaccurate rhythm classification by the algorithm of the defibrillator. The objective of this study was to design ...