1
Using Mel-Spectrograms and 2D-CNNs to Detect Murmurs in Variable Length Phonocardiograms
2
Transformer Embedded with Learnable Filters for Heart Murmur Detection
3
Detection of Heart Sound Murmurs and Clinical Outcome with Bidirectional Long Short-Term Memory Networks
4
Heart Murmur Detection Using Wavelet Time Scattering and Support Vector Machines
5
Classification of Phonocardiograms Using Residual Convolutional Neural Network and MLP
6
Classification of Phonocardiogram Recordings Using Vision Transformer Architecture
7
Phonocardiographic Murmur Detection by Scattering-Recurrent Networks
8
Heart Murmur Detection of PCG Using ResNet with Selective Kernel Convolution
9
Ensemble Transformer-Based Neural Networks Detect Heart Murmur in Phonocardiogram Recordings
10
Outcome Prediction and Murmur Detection in Sets of Phonocardiograms by a Deep Learning-Based Ensemble Approach
11
Deep Learning Based Heart Murmur Detection Using Frequency-time Domain Features of Heartbeat Sounds
12
Classification of Murmurs in PCG Using Combined Frequency Domain and Physician Inspired Features
13
Heart Murmur Detection from Phonocardiogram Based on Residual Neural Network with Classes Distinguished Focal Loss
14
Transfer Learning in Heart Sound Classification using Mel Spectrogram
15
Murmur Classification with U-net State Prediction
16
Detection of Heart Murmurs in Phonocardiograms with Parallel Hidden Semi-Markov Models
17
Searching for Effective Neural Network Architectures for Heart Murmur Detection from Phonocardiogram
18
Learning Time-Frequency Representations of Phonocardiogram for Murmur Detection
19
Heart Murmur Detection and Clinical Outcome Prediction Using Multilayer Perceptron Classifier
20
Multi-Task Prediction of Murmur and Outcome from Heart Sound Recordings
21
Murmur Identification Using Supervised Contrastive Learning
22
Murmur Detection and Clinical Outcome Classification Using a VGG-like Network and Combined Time-Frequency Representations of PCG Signals
23
A Fusion of Handcrafted Feature-Based and Deep Learning Classifiers for Heart Murmur Detection
24
Phonocardiogram Classification Using 1-Dimensional Inception Time Convolutional Neural Networks
25
Dual Bayesian ResNet: A Deep Learning Approach to Heart Murmur Detection
26
An LSTM-based Listener for Early Detection of Heart Disease
27
A Lightweight Robust Approach for Automatic Heart Murmurs and Clinical Outcomes Classification from Phonocardiogram Recordings
28
Two-Stage Multitask-Learner for PCG Murmur Location Detection
29
Beat-wise Uncertainty Learning for Murmur Detection in Heart Sounds
30
Convolutional Neural Network Approach for Heart Murmur Sound Detection in Auscultation Signals Using Wavelet Transform Based Features
31
ACQuA: Anomaly Classification with Quasi-Attractors
32
Towards Uncertainty-Aware Murmur Detection in Heart Sounds via Tandem Learning
33
Detection of Murmurs from Heart Sound Recordings with Deep Residual Networks
34
Hierarchical Multi-Scale Convolutional Network for Murmurs Detection on PCG Signals
35
Maiby's Algorithm: A Two-Stage Deep Learning Approach for Murmur Detection in Mel Spectrograms for Automatic Auscultation of Congenital Heart Disease
36
Rethinking Algorithm Performance Metrics for Artificial Intelligence in Diagnostic Medicine.
37
The CirCor DigiScope Dataset: From Murmur Detection to Murmur Classification
38
On the Inequity of Predicting A While Hoping for B
39
The Clinical Significance of the Systolic Murmur
40
Early Prediction of Sepsis From Clinical Data: The PhysioNet/Computing in Cardiology Challenge 2019
41
Adaptive Sojourn Time HSMM for Heart Sound Segmentation
42
Deep Convolutional Neural Networks for Heart Sound Segmentation
43
AF classification from a short single lead ECG recording: The PhysioNet/computing in cardiology challenge 2017
44
The Diagnostic Utility of Computer-Assisted Auscultation for the Early Detection of Cardiac Murmurs of Structural Origin in the Periodic Health Evaluation
45
An open access database for the evaluation of heart sound algorithms
46
XGBoost: A Scalable Tree Boosting System
48
Cardiac auscultation: rediscovering the lost art.
49
Computer aided analysis of phonocardiogram
50
Relationship between accurate auscultation of a clinically useful third heart sound and level of experience.
52
Greedy function approximation: A gradient boosting machine.
55
Encyclopedia of Medical Devices and Instrumentation
56
Interobserver agreement by auscultation in the presence of a third heart sound in patients with congestive heart failure.
58
Listen to your heart: A self-supervised approach for detecting murmur in heart-beat sounds for the Physionet 2022 challenge
59
Heart Murmur Detection from Phono-cardiogramRecordings: The George B. Moody PhysioNetChallenge2022
60
Two-stage Detection of Murmurs from Phonocardiograms using Deep and One-class Methods
61
Classificationof heart murmurs using an ensembleof residualCNNs
62
Modified Variable Kernel Length ResNets for Heart Murmur Detection and Clinical Outcome Prediction using Multi-positional Phonocardiogram Recording
66
Features for Heartbeat Sound Signal Normal and Pathological
68
Physionet: components of a new research resource for complex physiologic signals
71
Data curation: Matthew A. Reyna, Andoni Elola, Jorge Oliveira, Francesco Renna, Sandra Mattos, Miguel T. Coimbra, Reza Sameni, Ali Bahrami Rad
72
Supervision: Matthew A. Reyna, Sandra Mattos, Miguel T. Coimbra, Reza Sameni, Ali Bahrami Rad, Gari D. Clifford
