AIMC Topic: Heart Auscultation
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Multiscale analysis of heart sound signals in the wavelet domain for heart murmur detection.
Scientific reports
Mar 25, 2025
A heart murmur is an atypical sound produced by blood flow through the heart. It can indicate a serious heart condition, so detecting heart murmurs is critical for identifying and managing cardiovascular diseases. However, current methods for identif...
External evaluation of a commercial artificial intelligence-augmented digital auscultation platform in valvular heart disease detection using echocardiography as reference standard.
International journal of cardiology
Oct 19, 2024
OBJECTIVE: There are few studies evaluating the accuracy of commercially available AI-powered digital auscultation platforms in detecting valvular heart disease (VHD). Therefore, the utility of these systems for diagnosing clinically significant VHD ...
Fed-MStacking: Heterogeneous Federated Learning With Stacking Misaligned Labels for Abnormal Heart Sound Detection.
IEEE journal of biomedical and health informatics
Sep 5, 2024
Ubiquitous sensing has been widely applied in smart healthcare, providing an opportunity for intelligent heart sound auscultation. However, smart devices contain sensitive information, raising user privacy concerns. To this end, federated learning (F...
Identifying pediatric heart murmurs and distinguishing innocent from pathologic using deep learning.
Artificial intelligence in medicine
Apr 4, 2024
OBJECTIVE: To develop a deep learning algorithm to perform multi-class classification of normal pediatric heart sounds, innocent murmurs, and pathologic murmurs.
Identification of Congenital Valvular Murmurs in Young Patients Using Deep Learning-Based Attention Transformers and Phonocardiograms.
IEEE journal of biomedical and health informatics
Apr 4, 2024
One in every four newborns suffers from congenital heart disease (CHD) that causes defects in the heart structure. The current gold-standard assessment technique, echocardiography, causes delays in the diagnosis owing to the need for experts who vary...
Deep Learning Algorithms to Detect Murmurs Associated With Structural Heart Disease.
Journal of the American Heart Association
Oct 13, 2023
Background The success of cardiac auscultation varies widely among medical professionals, which can lead to missed treatments for structural heart disease. Applying machine learning to cardiac auscultation could address this problem, but despite rece...
Cardiac auscultation predicts mortality in elderly patients admitted for COVID-19.
Hospital practice (1995)
Apr 29, 2022
INTRODUCTION: COVID-19 has had a great impact on the elderly population. All admitted patients underwent cardiac auscultation at the Emergency Department. However, to our knowledge, there is no literature that explains the implications of cardiac aus...
Deep Learning Algorithm for Automated Cardiac Murmur Detection via a Digital Stethoscope Platform.
Journal of the American Heart Association
Apr 26, 2021
Background Clinicians vary markedly in their ability to detect murmurs during cardiac auscultation and identify the underlying pathological features. Deep learning approaches have shown promise in medicine by transforming collected data into clinical...
Automatic recognition of murmurs of ventricular septal defect using convolutional recurrent neural networks with temporal attentive pooling.
Scientific reports
Dec 11, 2020
Recognizing specific heart sound patterns is important for the diagnosis of structural heart diseases. However, the correct recognition of heart murmur depends largely on clinical experience. Accurately identifying abnormal heart sound patterns is ch...
Artificial Intelligence-Assisted Auscultation of Heart Murmurs: Validation by Virtual Clinical Trial.
Pediatric cardiology
Dec 12, 2018
Artificial intelligence (AI) has potential to improve the accuracy of screening for valvular and congenital heart disease by auscultation. However, despite recent advances in signal processing and classification algorithms focused on heart sounds, cl...
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