Deep autoencoder neural networks for heart sound classification
Heart sound signals, or Phonocardiogram (PCG), play a significant role in diagnosing heart
diseases, and it is a well-accepted way to detect cardiovascular diseases (CVDs). Recent …
diseases, and it is a well-accepted way to detect cardiovascular diseases (CVDs). Recent …
[PDF][PDF] Data augmentation and the improvement of the performance of convolutional neural networks for heart sound classification
S Takezaki, K Kishida - IAENG Int. J. Comput. Sci, 2022 - iaeng.org
The effective management and early diagnosis of cardiovascular diseases (CVDs) are
crucial to bring down the mortality associated these diseases. Because detecting CVDs can …
crucial to bring down the mortality associated these diseases. Because detecting CVDs can …
Phonocardiogram classification using deep convolutional neural networks with majority vote strategy
Most current automated phonocardiogram (PCG) classification methods are relied on PCG
segmentation. It is universal to make use of the segmented PCG signals and then extract …
segmentation. It is universal to make use of the segmented PCG signals and then extract …
[HTML][HTML] Heart Sound Classification Using Wavelet Analysis Approaches and Ensemble of Deep Learning Models
Analyzing the condition and function of the heart is very important because cardiovascular
diseases (CVDs) are responsible for high mortality rates worldwide and can lead to strokes …
diseases (CVDs) are responsible for high mortality rates worldwide and can lead to strokes …
Automated heart sound classification system from unsegmented phonocardiogram (PCG) using deep neural network
PT Krishnan, P Balasubramanian… - Physical and Engineering …, 2020 - Springer
Given the patient to doctor ratio of 50,000: 1 in low income and middle-income countries,
there is a need for automated heart sound classification system that can screen the …
there is a need for automated heart sound classification system that can screen the …
[HTML][HTML] Automatic classification of normal–abnormal heart sounds using convolution neural network and long-short term memory
The phonocardiogram (PCG) is an important analysis method for the diagnosis of
cardiovascular disease, which is usually performed by experienced medical experts. Due to …
cardiovascular disease, which is usually performed by experienced medical experts. Due to …
Accurate classification of heart sound signals for cardiovascular disease diagnosis by wavelet analysis and convolutional neural network: preliminary results
Heart sound (HS) signals contain valuable diagnostic information for detection of heart
abnormalities. The early detection of heart abnormalities plays an important role in reducing …
abnormalities. The early detection of heart abnormalities plays an important role in reducing …
Deep learning for heart sounds classification using scalograms and automatic segmentation of PCG signals
J Gelpud, S Castillo, M Jojoa, B Garcia-Zapirain… - … : 16th International Work …, 2021 - Springer
This paper proposes a set of Deep Learning algorithms for classifying Phonocardiogram
(PCG) scalogram. PCG signals contain valuable information about the heart health status …
(PCG) scalogram. PCG signals contain valuable information about the heart health status …
PCTMF-Net: heart sound classification with parallel CNNs-transformer and second-order spectral analysis
Heart disease is a common condition worldwide and has become one of the leading causes
of death worldwide. The electrocardiogram (PCG) is a safe, painless, and non-invasive test …
of death worldwide. The electrocardiogram (PCG) is a safe, painless, and non-invasive test …
Classification of Heart Sounds Using Multi-Branch Deep Convolutional Network and LSTM-CNN
SA Latifi, H Ghassemian, M Imani - arXiv preprint arXiv:2407.10689, 2024 - arxiv.org
This paper presents a fast and cost-effective method for diagnosing cardiac abnormalities
with high accuracy and reliability using low-cost systems in clinics. The primary limitation of …
with high accuracy and reliability using low-cost systems in clinics. The primary limitation of …