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Heart Sounds

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[A heart sound classification method based on complete ensemble empirical modal decomposition with adaptive noise permutation entropy and support vector machine].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Heart sound signal is a kind of physiological signal with nonlinear and nonstationary features. In order to improve the accuracy and efficiency of the phonocardiogram (PCG) classification, a new method was proposed by means of support vector machine ...

Deep Time Growing Neural Network vs Convolutional Neural Network for Intelligent Phonocardiography.

Studies in health technology and informatics
This paper explores the capabilities of a sophisticated deep learning method, named Deep Time Growing Neural Network (DTGNN), and compares its possibilities against a generally well-known method, Convolutional Neural network (CNN). The comparison is ...

Accuracy of a Deep Learning Method for Heart Sound Analysis is Unrealistic.

Neural networks : the official journal of the International Neural Network Society

Heart sound classification based on equal scale frequency cepstral coefficients and deep learning.

Biomedizinische Technik. Biomedical engineering
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...

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
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...

Cutting Weights of Deep Learning Models for Heart Sound Classification: Introducing a Knowledge Distillation Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Cardiovascular diseases (CVDs) are the number one cause of death worldwide. In recent years, intelligent auxiliary diagnosis of CVDs based on computer audition has become a popular research field, and intelligent diagnosis technology is increasingly ...

Effects of precise cardio sounds on the success rate of phonocardiography.

PloS one
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
OBJECTIVE: To develop a deep learning algorithm to perform multi-class classification of normal pediatric heart sounds, innocent murmurs, and pathologic murmurs.

A Robust Deep Learning Framework Based on Spectrograms for Heart Sound Classification.

IEEE/ACM transactions on computational biology and bioinformatics
Heart sound analysis plays an important role in early detecting heart disease. However, manual detection requires doctors with extensive clinical experience, which increases uncertainty for the task, especially in medically underdeveloped areas. This...

Fed-MStacking: Heterogeneous Federated Learning With Stacking Misaligned Labels for Abnormal Heart Sound Detection.

IEEE journal of biomedical and health informatics
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...