Convolutional and recurrent neural networks for the detection of valvular heart diseases in phonocardiogram recordings
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Convolutional and recurrent neural networks for the detection of valvular heart diseases in phonocardiogram recordings
Authors
Keywords
Cardiovascular disease (CVD), Valvular heart diseases (CHD), Phonocardiography (PCG), Heart sounds recordings, Deep learning, Convolutional neural networks (CNN), Bi-directional long short-term memory (BiLSTM), Training and classification
Journal
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Volume 200, Issue -, Pages 105940
Publisher
Elsevier BV
Online
2021-01-18
DOI
10.1016/j.cmpb.2021.105940
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Automated detection of heart valve diseases using chirplet transform and multiclass composite classifier with PCG signals
- (2020) Samit Kumar Ghosh et al. COMPUTERS IN BIOLOGY AND MEDICINE
- An Automatic Diagnosis of Arrhythmias Using a Combination of CNN and LSTM Technology
- (2020) Zhenyu Zheng et al. Electronics
- Classification of Heart Sounds Using Convolutional Neural Network
- (2020) Fan Li et al. Applied Sciences-Basel
- Applying an ensemble convolutional neural network with Savitzky–Golay filter to construct a phonocardiogram prediction model
- (2019) Jimmy Ming-Tai Wu et al. APPLIED SOFT COMPUTING
- Heart sounds classification using a novel 1-D convolutional neural network with extremely low parameter consumption
- (2019) Bin Xiao et al. NEUROCOMPUTING
- A Brief Review of Cardiovascular Diseases, Associated Risk Factors and Current Treatment Regimes
- (2019) Gagan D. Flora et al. CURRENT PHARMACEUTICAL DESIGN
- Heartbeat Sound Signal Classification Using Deep Learning
- (2019) Ali Raza et al. SENSORS
- Heart Disease and Stroke Statistics—2018 Update: A Report From the American Heart Association
- (2018) Emelia J. Benjamin et al. CIRCULATION
- Murmur clinic: validation of a new model for detecting heart valve disease
- (2018) Jane Draper et al. HEART
- Classification of Heart Sound Signal Using Multiple Features
- (2018) Yaseen et al. Applied Sciences-Basel
- An open access database for the evaluation of heart sound algorithms
- (2016) Chengyu Liu et al. PHYSIOLOGICAL MEASUREMENT
- Pathophysiology of valvular heart disease
- (2016) YI ZENG et al. Experimental and Therapeutic Medicine
- Mapping the Risk of Snakebite in Sri Lanka - A National Survey with Geospatial Analysis
- (2016) Dileepa Senajith Ediriweera et al. PLoS Neglected Tropical Diseases
- How herbivores coopt plant defenses: natural selection, specialization, and sequestration
- (2016) Georg Petschenka et al. Current Opinion in Insect Science
- A novel hybrid energy fraction and entropy-based approach for systolic heart murmurs identification
- (2015) Yineng Zheng et al. EXPERT SYSTEMS WITH APPLICATIONS
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Point-of-care cardiac ultrasound in acute medicine - the quick scan
- (2014) S. S. Hothi et al. CLINICAL MEDICINE
- Valvular Heart Disease: Classic Teaching and Emerging Paradigms
- (2013) D. Marshall Brinkley et al. AMERICAN JOURNAL OF MEDICINE
- The Framingham Heart Study and the epidemiology of cardiovascular disease: a historical perspective
- (2013) Syed S Mahmood et al. LANCET
- Triggers for Surgical Referral in Degenerative Mitral Valve Regurgitation
- (2012) Shinobu Itagaki et al. CIRCULATION JOURNAL
- Calcific Aortic Valve Disease: Not Simply a Degenerative Process
- (2011) Nalini M. Rajamannan et al. CIRCULATION
- Valvular heart disease: the next cardiac epidemic
- (2010) J. L. d'Arcy et al. HEART
- Cardiac sound murmurs classification with autoregressive spectral analysis and multi-support vector machine technique
- (2009) Samjin Choi et al. COMPUTERS IN BIOLOGY AND MEDICINE
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started