AIMC Topic: Heart Sounds
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Effects of precise cardio sounds on the success rate of phonocardiography.
PloS one
Jul 15, 2024
This work investigates whether inclusion of the low-frequency components of heart sounds can increase the accuracy, sensitivity and specificity of diagnosis of cardiovascular disorders. We standardized the measurement method to minimize changes in si...
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.
Design of ear-contactless stethoscope and improvement in the performance of deep learning based on CNN to classify the heart sound.
Medical & biological engineering & computing
Apr 27, 2023
Cardiac-related disorders are rapidly growing throughout the world. Accurate classification of cardiovascular diseases is an important research topic in healthcare. During COVID-19, auscultating heart sounds was challenging as health workers and doct...
Heart sound classification based on equal scale frequency cepstral coefficients and deep learning.
Biomedizinische Technik. Biomedical engineering
Feb 15, 2023
Heart diseases represent a serious medical condition that can be fatal. Therefore, it is critical to investigate the measures of its early prevention. The Mel-scale frequency cepstral coefficients (MFCC) feature has been widely used in the early diag...
Accuracy of a Deep Learning Method for Heart Sound Analysis is Unrealistic.
Neural networks : the official journal of the International Neural Network Society
Dec 13, 2022
The Effect of Signal Duration on the Classification of Heart Sounds: A Deep Learning Approach.
Sensors (Basel, Switzerland)
Mar 15, 2022
Deep learning techniques are the future trend for designing heart sound classification methods, making conventional heart sound segmentation dispensable. However, despite using fixed signal duration for training, no study has assessed its effect on t...
Deep learning-based computer-aided heart sound analysis in children with left-to-right shunt congenital heart disease.
International journal of cardiology
Dec 10, 2021
OBJECTIVE: The purpose of this study was to explore a new algorithm model capable of leverage deep learning to screen and diagnose specific types of left-to-right shunt congenital heart disease (CHD) in children.
A novel multi-branch architecture for state of the art robust detection of pathological phonocardiograms.
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Oct 25, 2021
Heart auscultation is an inexpensive and fundamental technique to effectively diagnose cardiovascular disease. However, due to relatively high human error rates even when auscultation is performed by an experienced physician, and due to the not unive...
Domain Generalization in Biosignal Classification.
IEEE transactions on bio-medical engineering
May 21, 2021
OBJECTIVE: When training machine learning models, we often assume that the training data and evaluation data are sampled from the same distribution. However, this assumption is violated when the model is evaluated on another unseen but similar databa...
Identification of Heart Sounds with an Interpretable Evolving Fuzzy Neural Network.
Sensors (Basel, Switzerland)
Nov 12, 2020
Heart problems are responsible for the majority of deaths worldwide. The use of intelligent techniques to assist in the identification of existing patterns in these diseases can facilitate treatments and decision making in the field of medicine. This...
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