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Automated detection of arrhythmias using different intervals of tachycardia ECG segments with convolutional neural network
Classification of normal and tachycardia arrhythmias ECG segments.Two and five seconds ECG segments are considered.Convolutional neural network is employed.QRS detection is not performed.Accuracy ofExpand
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Application of deep convolutional neural network for automated detection of myocardial infarction using ECG signals
The electrocardiogram (ECG) is a useful diagnostic tool to diagnose various cardiovascular diseases (CVDs) such as myocardial infarction (MI). The ECG records the heart's electrical activity andExpand
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An efficient binary Salp Swarm Algorithm with crossover scheme for feature selection problems
Abstract Searching for the (near) optimal subset of features is a challenging problem in the process of feature selection (FS). In the literature, Swarm Intelligence (SI) algorithms show superiorExpand
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Automated detection and localization of myocardial infarction using electrocardiogram: a comparative study of different leads
Identification and timely interpretation of changes occurring in the 12 electrocardiogram (ECG) leads is crucial to identify the types of myocardial infarction (MI). However, manual annotation ofExpand
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A hybrid approach to the sentiment analysis problem at the sentence level
The objective of this article is to present a hybrid approach to the Sentiment Analysis problem at the sentence level. This new method uses natural language processing (NLP) essential techniques, aExpand
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Towards felicitous decision making: An overview on challenges and trends of Big Data
The era of Big Data has arrived along with large volume, complex and growing data generated by many distinct sources. Nowadays, nearly every aspect of the modern society is impacted by Big Data,Expand
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An integrated index for detection of Sudden Cardiac Death using Discrete Wavelet Transform and nonlinear features
Display Omitted Novel Sudden Cardiac Death Index (SCDI) is proposed using ECG signals.Nonlinear features are extracted from DWT coefficients.SCDI is formulated using nonlinear features.SCDI predictsExpand
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Automated detection of atrial fibrillation using long short-term memory network with RR interval signals
Atrial Fibrillation (AF), either permanent or intermittent (paroxysnal AF), increases the risk of cardioembolic stroke. Accurate diagnosis of AF is obligatory for initiation of effective treatment toExpand
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Application of entropies for automated diagnosis of epilepsy using EEG signals: A review
Epilepsy can be detected using EEG signals.The entropy indicates the complexity of the EEG signal.Various entropies are used to diagnose epilepsy.Unique ranges for various entropies are proposed.Expand
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Sudden cardiac death (SCD) prediction based on nonlinear heart rate variability features and SCD index
SCD is predicated using SVM classifier and sudden cardiac death index (SCDI).Nonlinear features are extracted from HRV signals.SVM predicts SCD with 94.7% accuracy four minutes before its onset.SCDIExpand
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