Heart Diseases Diagnosis Using Intelligent Algorithm Based on PCG Signal Analysis

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Circuits and Systems

ISSN Print: 2153-1285
ISSN Online: 2153-1293
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"Heart Diseases Diagnosis Using Intelligent Algorithm Based on PCG Signal Analysis"
written by Mohammed Nabih-Ali, El-Sayed A. El-Dahshan, Ashraf S. Yahia,
published by Circuits and Systems, Vol.8 No.7, 2017

has been cited by the following article(s):

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[1]	Abnormal Heart Sound Detection using Time-Frequency Analysis and Machine Learning Techniques
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[2]	Detection of Myocardial Infarction in Coronary Artery Disease Patients Based on Phonocardiogram Signal Using Ensemble Learning
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[3]	Arousal detection by using ultra-short-term heart rate variability (HRV) analysis
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[4]	SAR-CardioNet: A Network for Heart Valve Disease Detection From PCG Signal Based on Split-Self Attention With Residual Paths
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[5]	The export operation mode and optimization strategy of crossborder e‐commerce enterprises integrating data mining algorithms
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[6]	Automated Detection of Heart Murmurs From the PCG Signal Using Stationary Wavelet Transform
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[7]	Performance Analysis Of Dwt Based Denoising Of Vibration Signals: A Case Study Of Heart Sound Signals
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[8]	The Export Operation Mode and Optimization Strategy of Crossborder e-Commerce Enterprises Integrating Data Mining Algorithms
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[9]	Alienation Control Technology of Information Pushed by Intelligent Algorithms in Media Communication
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[10]	Hierarchical fusion in feature and decision space for detection of valvular heart disease using PCG signal
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[11]	Optimal Design of Computer Network Reliability based on PSO-Fcm Intelligent Algorithm
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[12]	FPGA Implementation of Low Power Pre-processor Design for Biomedical Signal Processing Application
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[13]	Classification of heart sounds associated with murmur for diagnosis of cardiac valve disorders
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[14]	Classification of cardiovascular diseases using dysphonia measurement in speech
	2021

[15]	Discrimination between patients with CVDs and healthy people by voiceprint using the MFCC and Pitch
	…, 2021

[16]	INVESTIGATION OF HEART ABNORMALITIES USING PHONOCARDIOGRAM SIGNAL
	2021

[17]	Phonocardiogram Classification Using Motif Discovery
	2021

[18]	Identification of ECG Anomalies Through Deep Deterministic Learning
	2020

[19]	طبقه‌بندی صداهای طبیعی و غیرطبیعی ضبط‌شده قلب با استفاده از آنالیز زمان-فرکانس سیگنال‌های ‌PCG‎
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[20]	Redes Neuronais Pré-Treinadas na Classificação Automática de Sons Cardíacos
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[21]	Classification and evaluation of the severity of tricuspid regurgitation using phonocardiogram
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[22]	Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network
	2020

[23]	Time-Frequency Analysis, Denoising, Compression, Segmentation, and Classification of PCG Signals
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[24]	Classification of heart sound short records using bispectrum analysis approach images and deep learning
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[25]	Mobile Solution for Early Detection of Heart Diseases using Artificial Intelligence and Novel Digital Stethoscope
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[26]	An Efficient Computational Approach for Phonocardiogram Signals Analysis and Normal/Abnormal heart sounds diagnosis
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[27]	Análise de som cardíaco pediátrico para identificação de sopro
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[28]	Sheet-type Device for Unconstrained Heart Sound Measurement and White Noise Reduction by Wiener Filter
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[29]	Classification of Normal/Abnormal Heart Sound Recordings Using Time–Frequency PCG Signal Analysis
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[30]	A Low Power Wearable ECG Module for Heart Rate Variability Classification System
	2020

[31]	Automatic Phonocardiography Analysis using Multi-Resolution Analysis Algorithm Based on Discrete Wavelet Transform
	2019

[32]	Construction of Fuzzy System for Classification of Heart Disease Based on Phonocardiogram Signal
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[33]	HOFSTEDE'NİN KÜLTÜR BOYUTLARININ KARADENİZ BÖLGESİ TURİZM ÇALIŞANLARI ÜZERİNDE İNCELENMESİ1
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[34]	Tek bir zamanla-değişen spektral nitelik kullanılarak kalp seslerinin hastalık tanısı amaçlı sınıflandırılması
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[35]	АВТОМАТИЗИРОВАННАЯ КЛАССИФИКАЦИЯ ФОНОКАРДИОГРАММ С ИСПОЛЬЗОВАНИЕМ ВЕЙВЛЕТ ПРЕОБРАЗОВАНИЯ
	… , медицинские, экологические системы и …, 2018

[36]	Localization and classification of heart beats in phonocardiography signals—A comprehensive review
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[37]	Deep Deterministic Learning for Pattern Recognition of Different Cardiac Diseases through the Internet of Medical Things
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[38]	Phonocardiogram signals processing approach for PASCAL Classifying Heart Sounds Challenge
	Signal, Image and Video Processing, 2018

[39]	A Novel Design and Development of Condenser Microphone Based Stethoscope to Analyze Phonocardiogram Spectrum Using Audacity
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[40]	АВТОМАТИЗИРОВАННАЯ КЛАССИФИКАЦИЯ ФОНОКАРДИОГРАММ С ИСПОЛЬЗОВАНИЕМ ВЕЙВЛЕТ-ПРЕОБРАЗОВАНИЯ
	2018

[1]	Abnormal Heart Sound Detection using Time-Frequency Analysis and Machine Learning Techniques Biomedical Signal Processing and Control, 2024 DOI:10.1016/j.bspc.2023.105899

[2]	Automated Detection of Heart Murmurs From the PCG Signal Using Stationary Wavelet Transform 2022 IEEE 19th India Council International Conference (INDICON), 2022 DOI:10.1109/INDICON56171.2022.10039806

[3]	Automated Detection of Heart Murmurs From the PCG Signal Using Stationary Wavelet Transform 2022 IEEE 19th India Council International Conference (INDICON), 2022 DOI:10.1109/INDICON56171.2022.10039806

[4]	Alienation Control Technology of Information Pushed by Intelligent Algorithms in Media Communication Computational Intelligence and Neuroscience, 2022 DOI:10.1155/2022/4855254

[5]	The Export Operation Mode and Optimization Strategy of Crossborder e-Commerce Enterprises Integrating Data Mining Algorithms Wireless Communications and Mobile Computing, 2022 DOI:10.1155/2022/6231249

[6]	Computational and Experimental Methods in Mechanical Engineering Smart Innovation, Systems and Technologies, 2022 DOI:10.1007/978-981-16-2857-3_48

[7]	Automated System for Features Extraction From PCG Signal 2021 5th International Conference on Computing Methodologies and Communication (ICCMC), 2021 DOI:10.1109/ICCMC51019.2021.9418229

[8]	Severity cardiac analysis using the Higher-order spectra Applied Mathematics and Computation, 2021 DOI:10.1016/j.amc.2021.126389

[9]	Severity cardiac analysis using the Higher-order spectra Applied Mathematics and Computation, 2021 DOI:10.1016/j.amc.2021.126389

[10]	Diagnosis of heart diseases by a secure Internet of Health Things system based on Autoencoder Deep Neural Network Computer Communications, 2020 DOI:10.1016/j.comcom.2020.08.011

[11]	Classification of heart sound short records using bispectrum analysis approach images and deep learning Network Modeling Analysis in Health Informatics and Bioinformatics, 2020 DOI:10.1007/s13721-020-00272-5

[12]	Classification and evaluation of the severity of tricuspid regurgitation using phonocardiogram Biomedical Signal Processing and Control, 2020 DOI:10.1016/j.bspc.2019.101688

[13]	Time-Frequency Analysis, Denoising, Compression, Segmentation, and Classification of PCG Signals IEEE Access, 2020 DOI:10.1109/ACCESS.2020.3020806

[14]	Phonocardiogram signals processing approach for PASCAL Classifying Heart Sounds Challenge Signal, Image and Video Processing, 2018 DOI:10.1007/s11760-018-1261-5

[15]	Localization and classification of heart beats in phonocardiography signals —a comprehensive review EURASIP Journal on Advances in Signal Processing, 2018 DOI:10.1186/s13634-018-0545-9

[16]	Deep Deterministic Learning for Pattern Recognition of Different Cardiac Diseases through the Internet of Medical Things Journal of Medical Systems, 2018 DOI:10.1007/s10916-018-1107-2

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