An automatic arrhythmia classification model based on improved Marine Predators Algorithm and Convolutions Neural Networks
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Yaser Maher Wazery | Essam H. Houssein | Diaa Salama Abd Elminaam | M. Hassaballah | Ibrahim E. Ibrahim | Ibrahim Elsayed Ibrahim | E. H. Houssein | Y. Wazery | M. Hassaballah
[1] Robertas Damasevicius,et al. COVID-19 image classification using deep features and fractional-order marine predators algorithm , 2020, Scientific Reports.
[2] Yuhui Shi,et al. Metaheuristic research: a comprehensive survey , 2018, Artificial Intelligence Review.
[3] Huazhong Yang,et al. A global and updatable ECG beat classification system based on recurrent neural networks and active learning , 2019, Inf. Sci..
[4] Jing Zhang,et al. ECG-based multi-class arrhythmia detection using spatio-temporal attention-based convolutional recurrent neural network , 2020, Artif. Intell. Medicine.
[5] John David Filmalter,et al. First Descriptions of the Behavior of Silky Sharks, Carcharhinus Falciformis, Around Drifting Fish Aggregating Devices in the Indian Ocean , 2011 .
[6] Navid Razmjooy,et al. A new configuration of autonomous CHP system based on improved version of marine predators algorithm: A case study , 2021 .
[7] Moncef Gabbouj,et al. Real-Time Patient-Specific ECG Classification by 1-D Convolutional Neural Networks , 2016, IEEE Transactions on Biomedical Engineering.
[8] Matin Hashemi,et al. ECG Classification Algorithm Based on STDP and R-STDP Neural Networks for Real-Time Monitoring on Ultra Low-Power Personal Wearable Devices , 2019, IEEE Transactions on Biomedical Circuits and Systems.
[9] Ajith Abraham,et al. Heart disease detection using hybrid of bacterial foraging and particle swarm optimization , 2019, Evolving Systems.
[10] Rajeev Sharma,et al. Baseline wander and power line interference removal from ECG signals using eigenvalue decomposition , 2018, Biomed. Signal Process. Control..
[11] Nitesh V. Chawla,et al. SMOTE: Synthetic Minority Over-sampling Technique , 2002, J. Artif. Intell. Res..
[12] Taher A. Shehabeldeen,et al. Utilization of Random Vector Functional Link integrated with Marine Predators Algorithm for tensile behavior prediction of dissimilar friction stir welded aluminum alloy joints , 2020 .
[13] Chandan Chakraborty,et al. Cardiac decision making using higher order spectra , 2013, Biomed. Signal Process. Control..
[14] Masoud Daneshtalab,et al. A review on deep learning methods for ECG arrhythmia classification , 2020, Expert Syst. Appl. X.
[15] Essam H. Houssein,et al. A Hybrid Heartbeats Classification Approach Based on Marine Predators Algorithm and Convolution Neural Networks , 2021, IEEE Access.
[16] M Suchetha,et al. PSO optimized 1-D CNN-SVM architecture for real-time detection and classification applications , 2019, Comput. Biol. Medicine.
[17] Aboul Ella Hassanien,et al. Maximizing lifetime of large-scale wireless sensor networks using multi-objective whale optimization algorithm , 2019, Telecommun. Syst..
[18] Mahmoud Hassaballah,et al. A novel hybrid Harris hawks optimization and support vector machines for drug design and discovery , 2020, Comput. Chem. Eng..
[19] Nitesh V. Chawla,et al. Classification and knowledge discovery in protein databases , 2004, J. Biomed. Informatics.
[20] B. S. Harish,et al. Automated ECG Analysis for Localizing Thrombus in Culprit Artery Using Rule Based Information Fuzzy Network , 2020, Int. J. Interact. Multim. Artif. Intell..
[21] P. Rajesh Kumar,et al. An Efficient Optimized Feature Selection with Machine Learning Approach for ECG Biometric Recognition , 2020, IETE Journal of Research.
[22] U. Rajendra Acharya,et al. Automated diagnosis of arrhythmia using combination of CNN and LSTM techniques with variable length heart beats , 2018, Comput. Biol. Medicine.
[23] Essam H. Houssein,et al. Hybrid slime mould algorithm with adaptive guided differential evolution algorithm for combinatorial and global optimization problems , 2021, Expert Syst. Appl..
[24] I. Daubechies,et al. Factoring wavelet transforms into lifting steps , 1998 .
[25] Srinivas Kalyanapu,et al. Classification of ECG Heartbeat Arrhythmia: A Review , 2020 .
[26] Lu Cao,et al. Arrhythmia Classification Based on Multi-Domain Feature Extraction for an ECG Recognition System , 2016, Sensors.
[27] Nabil Neggaz,et al. An efficient ECG arrhythmia classification method based on Manta ray foraging optimization , 2021, Expert Syst. Appl..
[28] Ki H. Chon,et al. Atrial Fibrillation Detection Using an iPhone 4S , 2013, IEEE Transactions on Biomedical Engineering.
[29] Aboul Ella Hassanien,et al. A Hybrid EEG Signals Classification Approach Based on Grey Wolf Optimizer Enhanced SVMs for Epileptic Detection , 2017, AISI.
[30] Leandro Nunes de Castro,et al. The Clonal Selection Algorithm with Engineering Applications , 2011 .
[31] Mahmoud Hassaballah,et al. Lévy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems , 2020, Eng. Appl. Artif. Intell..
[32] Victor Hugo C. de Albuquerque,et al. A novel electrocardiogram feature extraction approach for cardiac arrhythmia classification , 2019, Future Gener. Comput. Syst..
[33] David E. Goldberg,et al. The compact genetic algorithm , 1999, IEEE Trans. Evol. Comput..
[34] Giuseppe De Pietro,et al. A deep learning approach for ECG-based heartbeat classification for arrhythmia detection , 2018, Future Gener. Comput. Syst..
[35] Bilal Alatas,et al. ACROA: Artificial Chemical Reaction Optimization Algorithm for global optimization , 2011, Expert Syst. Appl..
[36] Salah Kamel,et al. An improved Manta ray foraging optimizer for cost-effective emission dispatch problems , 2021, Eng. Appl. Artif. Intell..
[37] Ahmed A. Elngar,et al. A novel Black Widow Optimization algorithm for multilevel thresholding image segmentation , 2021, Expert Syst. Appl..
[38] Yilmaz Kaya,et al. 1D-local binary pattern based feature extraction for classification of epileptic EEG signals , 2014, Appl. Math. Comput..
[39] Alireza Karimi,et al. A lumped parameter mathematical model to analyze the effects of tachycardia and bradycardia on the cardiovascular system , 2015 .
[40] Hegazy Rezk,et al. Marine Predators Algorithm Optimized Reduced Sensor Fuzzy-Logic Based Maximum Power Point Tracking of Fuel Cell-Battery Standalone Applications , 2021, IEEE Access.
[41] Hany M. Hasanien,et al. Parameters identification of solid oxide fuel cell for static and dynamic simulation using comprehensive learning dynamic multi-swarm marine predators algorithm , 2021 .
[42] Nabil Neggaz,et al. Enhanced Harris hawks optimization with genetic operators for selection chemical descriptors and compounds activities , 2021, Neural Computing and Applications.
[43] U. Rajendra Acharya,et al. Automated heartbeat classification and detection of arrhythmia using optimal orthogonal wavelet filters , 2019, Informatics in Medicine Unlocked.
[44] Di Wang,et al. Automatic recognition of arrhythmia based on principal component analysis network and linear support vector machine , 2018, Comput. Biol. Medicine.
[45] Victor-Emil Neagoe,et al. A Neuro-Fuzzy Approach to Classification of ECG Signals for Ischemic Heart Disease Diagnosis , 2003, AMIA.
[46] Kemal Polat,et al. Detection of ECG Arrhythmia using a differential expert system approach based on principal component analysis and least square support vector machine , 2007, Appl. Math. Comput..
[47] Zong Woo Geem,et al. A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..
[48] Amir H. Gandomi,et al. Marine Predators Algorithm: A nature-inspired metaheuristic , 2020, Expert Syst. Appl..
[49] Zhengchun Hua,et al. Automated arrhythmia classification based on a combination network of CNN and LSTM , 2020, Biomed. Signal Process. Control..
[50] Victor Hugo C. de Albuquerque,et al. Heart Arrhythmia Classification Based on Statistical Moments and Structural Co-occurrence , 2019, Circuits, Systems, and Signal Processing.
[51] Ridha Ouni,et al. Electrocardiogram heartbeat classification based on a deep convolutional neural network and focal loss , 2020, Comput. Biol. Medicine.
[52] U. Rajendra Acharya,et al. Automated diagnosis of Coronary Artery Disease using nonlinear features extracted from ECG signals , 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).
[53] Annisa Darmawahyuni,et al. An Automated ECG Beat Classification System Using Deep Neural Networks with an Unsupervised Feature Extraction Technique , 2019, Applied Sciences.
[54] Kevin Kaergaard,et al. A comprehensive performance analysis of EEMD-BLMS and DWT-NN hybrid algorithms for ECG denoising , 2016, Biomed. Signal Process. Control..
[55] Jinsul Kim,et al. An Automated ECG Beat Classification System Using Convolutional Neural Networks , 2016, 2016 6th International Conference on IT Convergence and Security (ICITCS).
[56] Sandeep Raj,et al. Sparse representation of ECG signals for automated recognition of cardiac arrhythmias , 2018, Expert Syst. Appl..
[57] Seyedali Mirjalili,et al. SCA: A Sine Cosine Algorithm for solving optimization problems , 2016, Knowl. Based Syst..
[58] Mohamed Elhoseny,et al. Hybrid Harris hawks optimization with cuckoo search for drug design and discovery in chemoinformatics , 2020, Scientific Reports.
[59] Mohamed Elhoseny,et al. A Hybrid COVID-19 Detection Model Using an Improved Marine Predators Algorithm and a Ranking-Based Diversity Reduction Strategy , 2020, IEEE Access.
[60] Rohini K. Srihari,et al. Feature selection for text categorization on imbalanced data , 2004, SKDD.
[61] Chaoyi Pang,et al. A cascaded classifier for multi-lead ECG based on feature fusion , 2019, Comput. Methods Programs Biomed..
[62] Mohamed Hammad,et al. A novel two-dimensional ECG feature extraction and classification algorithm based on convolution neural network for human authentication , 2019, Future Gener. Comput. Syst..
[63] Nathalie Japkowicz,et al. The Class Imbalance Problem: Significance and Strategies , 2000 .
[64] Riccardo Poli,et al. Particle swarm optimization , 1995, Swarm Intelligence.
[65] R. Mehra. Global public health problem of sudden cardiac death. , 2007, Journal of electrocardiology.
[66] Min Zhou,et al. ECG Classification Using Wavelet Packet Entropy and Random Forests , 2016, Entropy.
[67] Ponnuthurai N. Suganthan,et al. Task Scheduling in Cloud Computing based on Meta-heuristics: Review, Taxonomy, Open Challenges, and Future Trends , 2021, Swarm Evol. Comput..
[68] Li Wan,et al. Heartbeat classification using deep residual convolutional neural network from 2-lead electrocardiogram. , 2019, Journal of electrocardiology.
[69] Enzo Pasquale Scilingo,et al. A tool for the real-time evaluation of ECG signal quality and activity: Application to submaximal treadmill test in horses , 2020, Biomed. Signal Process. Control..
[70] U. Rajendra Acharya,et al. Novel deep genetic ensemble of classifiers for arrhythmia detection using ECG signals , 2019, Neural Computing and Applications.
[71] Amir H. Gandomi,et al. Machine learning-based left ventricular hypertrophy detection using multi-lead ECG signal , 2020, Neural Computing and Applications.
[72] Antonia Papandreou-Suppappola,et al. Electrocardiogram Signal Modeling With Adaptive Parameter Estimation Using Sequential Bayesian Methods , 2014, IEEE Transactions on Signal Processing.
[73] Seyedali Mirjalili,et al. Henry gas solubility optimization: A novel physics-based algorithm , 2019, Future Gener. Comput. Syst..
[74] ZhengYu-Jun. Water wave optimization , 2015 .
[75] Mehmet Engin,et al. ECG beat classification using neuro-fuzzy network , 2004, Pattern Recognit. Lett..
[76] Aboul Ella Hassanien,et al. ECG signals classification: a review , 2017, Int. J. Intell. Eng. Informatics.
[77] Ruxin Wang,et al. Multi-class Arrhythmia detection from 12-lead varied-length ECG using Attention-based Time-Incremental Convolutional Neural Network , 2020, Inf. Fusion.
[78] U. Rajendra Acharya,et al. A deep convolutional neural network model to classify heartbeats , 2017, Comput. Biol. Medicine.