Results 181 to 190 of about 5,744 (245)

Cross-wavelet assisted convolution neural network (AlexNet) approach for phonocardiogram signals classification

Biomedical Signal Processing and Control, 2021
Priyadarshiny Dhar, S. Dutta, Vivek Mukherjee   +2 more
exaly   +2 more sources

Recognition of Pediatric Congenital Heart Diseases by Using Phonocardiogram Signals and Transformer-Based Neural Networks

Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2023
The phonocardiogram (PCG) or heart sound auscultation is a low-cost and non-invasive method to diagnose Congenital Heart Disease (CHD). However, recognizing CHD in the pediatric population based on heart sounds is difficult because it requires high ...
Md Hassanuzzaman, Nurul Akhtar Hasan, Mohammad Abdullah-Al-Mamun, M. Alkhodari, K. Ahmed, A. Khandoker, R. Mostafa   +6 more
semanticscholar   +1 more source

A fusion framework based on multi-domain features and deep learning features of phonocardiogram for coronary artery disease detection

Computers in Biology and Medicine, 2020
Jonghun Yoon, Xinpei Wang, Changchun Liu
exaly   +2 more sources

Parameter-Efficient Densely Connected Dual Attention Network for Phonocardiogram Classification

IEEE journal of biomedical and health informatics, 2023
Cardiac auscultation, exhibited by phonocardiogram (PCG), is a non-invasive and low-cost diagnostic method for cardiovascular diseases (CVDs). However, deploying it in practice is quite challenging, due to the inherent murmurs and a limited number of ...
Keying Ma, Jianbo Lu, B. Lu
semanticscholar   +1 more source

Detection of Phonocardiogram Event Patterns in Mitral Valve Prolapse: An Automated Clinically Relevant Explainable Diagnostic Framework

IEEE Transactions on Instrumentation and Measurement, 2023
The objective of this study is to develop an automated clinically relevant diagnostic framework for a group of cardiovascular diseases, namely, valvular heart diseases (VHDs).
Rajeshwari B. S., Madhurima Patra, Aman Sinha, Arnab Sengupta, N. Ghosh   +4 more
semanticscholar   +1 more source

Ensembled Transfer Learning and Multiple Kernel Learning for Phonocardiogram Based Atherosclerotic Coronary Artery Disease Detection

IEEE journal of biomedical and health informatics, 2022
Conventional machine learning has paved the way for a simple, affordable, non-invasive approach for Coronary artery disease (CAD) detection using phonocardiogram (PCG).
Akanksha Pathak, K. Mandana, G. Saha
semanticscholar   +1 more source

Applying an ensemble convolutional neural network with Savitzky–Golay filter to construct a phonocardiogram prediction model

Applied Soft Computing Journal, 2019
Jimmy Ming-tai Wu, Meng-hsiun Tsai, Sk Hafizul Islam   +2 more
exaly   +2 more sources

The phonocardiogram exercise test

IEEE Engineering in Medicine and Biology Magazine, 1999
Cardiovascular disease is the leading killer and the major cause of disability in adults. Detection and analysis of heart sounds is an important (and economical) method that can be used to determine the state of the heart and great vessels. In this article we present a newly developed technique for detecting cardiac reserve in both healthy and diseased
Jianhua Pei, Yihua Xiao, Shouzhong Xiao, Shiyong Zhou, Cao Zehan   +4 more
openaire   +3 more sources

Automatic segmentation for neonatal phonocardiogram

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021
This work addresses the automatic segmentation of neonatal phonocardiogram (PCG) to be used in the artificial intelligence-assisted diagnosis of abnormal heart sounds. The proposed novel algorithm has a single free parameter - the maximum heart rate. The algorithm is compared with the baseline algorithm, which was developed for adult PCG segmentation ...
Sergi, Gomez-Quintana, Ihor, Shelevytsky, Victoriya, Shelevytska, Emanuel, Popovici, Andriy, Temko   +4 more
openaire   +2 more sources

Fetal phonocardiogram signals denoising using improved complete ensemble (EMD) with adaptive noise and optimal thresholding of wavelet coefficients

Biomedizinische Technik. Biomedical engineering, 2022
Although fetal phonocardiogram (fPCG) signals have become a good indicator for discovered heart disease, they may be contaminated by various noises that reduce the signals quality and the final diagnosis decision.
Fethi Cheikh, Nasser Edinne Benhassine, S. Sbaa   +2 more
semanticscholar   +1 more source