Journal of Biomedical Science and Engineering

Journal of Biomedical Science and Engineering

ISSN Print: 1937-6871
ISSN Online: 1937-688X
www.scirp.org/journal/jbise
E-mail: jbise@scirp.org
"Detection of Ventricular Fibrillation Using Random Forest Classifier"
written by Anurag Verma, Xiaodai Dong,
published by Journal of Biomedical Science and Engineering, Vol.9 No.5, 2016
has been cited by the following article(s):
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[2] Machine learning-data mining integrated approach for premature ventricular contraction prediction
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[3] Deep Neural Network Approach for Continuous ECG‐Based Automated External Defibrillator Shock Advisory System During Cardiopulmonary Resuscitation
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[4] Recognition of dangerous rhythm disturbances from short ECG fragments
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[5] DETECTION OF VENTRICULAR FIBRILLATION USING WAVELET TRANSFORM AND PHASE SPACE RECONSTRUCTION FROM ECG SIGNALS
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[6] ECG Database for Evaluating the Efficiency of Recognizing Dangerous Arrhythmias
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[7] Recognition of the Life-Threatening Cardiac Arrhythmias in the Frequency Domain
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[8] Discrimination of Life-Threatening Arrhythmias Using Singular Value, Harmonic Phase Distribution, and Dynamic Time Warping of ECG Signals
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[9] Intelligent Analysis of Biomedical Signals for Personal Identification and Life Support Systems
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[10] Recognition of Arrhythmias Based on the Spectral Description of ECG
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[11] Интеллектуальный анализ аритмий по спектральному описанию электрокардиосигнала
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[12] VT/VF Detection Method Based On ECG Signal Quality Assessment
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[13] VFPred: A Fusion of Signal Processing and Machine Learning techniques in Detecting Ventricular Fibrillation from ECG Signals
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[14] Automated Method for Discrimination of Arrhythmias Using Time, Frequency, and Nonlinear Features of Electrocardiogram Signals
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[15] Detection of Ventricular Fibrillation Using the Image from Time-Frequency Representation and Combined Classifiers without Feature Extraction
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