AIMC Topic: Heart Sounds

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Cutting Weights of Deep Learning Models for Heart Sound Classification: Introducing a Knowledge Distillation Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Cardiovascular diseases (CVDs) are the number one cause of death worldwide. In recent years, intelligent auxiliary diagnosis of CVDs based on computer audition has become a popular research field, and intelligent diagnosis technology is increasingly ...
Humans Neural Networks, Computer Wearable Electronic Devices Heart Sounds Cardiovascular Diseases Deep Learning
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Deep Time Growing Neural Network vs Convolutional Neural Network for Intelligent Phonocardiography.

Studies in health technology and informatics Jun 29, 2022
This paper explores the capabilities of a sophisticated deep learning method, named Deep Time Growing Neural Network (DTGNN), and compares its possibilities against a generally well-known method, Convolutional Neural network (CNN). The comparison is ...
Heart Sounds Phonocardiography Humans Neural Networks, Computer Deep Learning Heart Diseases
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[A heart sound classification method based on complete ensemble empirical modal decomposition with adaptive noise permutation entropy and support vector machine].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Apr 25, 2022
Heart sound signal is a kind of physiological signal with nonlinear and nonstationary features. In order to improve the accuracy and efficiency of the phonocardiogram (PCG) classification, a new method was proposed by means of support vector machine ...
Support Vector Machine Entropy Heart Sounds Signal Processing, Computer-Assisted Signal-To-Noise Ratio
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Segmentation-free Heart Pathology Detection Using Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Nov 1, 2021
Cardiovascular (CV) diseases are the leading cause of death in the world, and auscultation is typically an essential part of a cardiovascular examination. The ability to diagnose a patient based on their heart sounds is a rather difficult skill to ma...
Neural Networks, Computer Deep Learning Humans Heart Sounds Wavelet Analysis Heart Auscultation
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[Classification of heart sound signals in congenital heart disease based on convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Oct 25, 2019
Cardiac auscultation is the basic way for primary diagnosis and screening of congenital heart disease(CHD). A new classification algorithm of CHD based on convolution neural network was proposed for analysis and classification of CHD heart sounds in ...
Heart Sounds Neural Networks, Computer Algorithms Sensitivity and Specificity Heart Defects, Congenital Humans
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Fundamental Heart Sound Classification using the Continuous Wavelet Transform and Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
Correct identification of the fundamental heart sounds is an important step in identifying the heart cycle stages. Heart valve pathologies can cause abnormal heart sounds or extra sounds, and an important distinguishing feature between different path...
Humans Neural Networks, Computer Heart Sounds Support Vector Machine Wavelet Analysis
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Crackle and Breathing Phase Detection in Lung Sounds with Deep Bidirectional Gated Recurrent Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
In this paper, we present a method for event detection in single-channel lung sound recordings. This includes the detection of crackles and breathing phase events (inspiration/expiration). Therefore, we propose an event detection approach with spectr...
Heart Sounds Respiration Respiratory Sounds Neural Networks, Computer Sound Lung Humans Sound Spectrography
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Structural Risk Evaluation of a Deep Neural Network and a Markov Model in Extracting Medical Information from Phonocardiography.

Studies in health technology and informatics Jan 1, 2018
This paper presents a method for exploring structural risk of any artificial intelligence-based method in bioinformatics, the A-Test method. This method provides a way to not only quantitate the structural risk associated with a classification method...
Heart Sounds Phonocardiography Risk Assessment Computational Biology Artificial Intelligence Algorithms Humans Neural Networks, Computer
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S1 and S2 Heart Sound Recognition Using Deep Neural Networks.

IEEE transactions on bio-medical engineering Feb 1, 2017
OBJECTIVE: This study focuses on the first (S1) and second (S2) heart sound recognition based only on acoustic characteristics; the assumptions of the individual durations of S1 and S2 and time intervals of S1-S2 and S2-S1 are not involved in the rec...
Signal Processing, Computer-Assisted Stethoscopes Female Humans Male Neural Networks, Computer Heart Auscultation Heart Sounds
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A Decision Support System for Cardiac Disease Diagnosis Based on Machine Learning Methods.

Studies in health technology and informatics Jan 1, 2017
This paper proposes a decision support system for screening pediatric cardiac disease in primary healthcare centres relying on the heart sound time series analysis. The proposed system employs our processing method which is based on the hidden Markov...
Heart Defects, Congenital Software Humans Heart Sounds Decision Support Systems, Clinical Machine Learning
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