Research process on deep learning methods for heart sounds classification

Journal Title: Progress in Medical Devices - Year 2023, Vol 1, Issue 2

Abstract

Cardiovascular diseases are still the primary threats to people’s health around the world. Automatic heart sound classification technology, as a fast and efficient means for diagnosis and treatment, is of great clinical significance. With the rapid development of artificial intelligence technology, deep learning algorithms are widely used in automatic heart sound classification. This paper reviewed the key technologies related to the automatic classification of heart sounds in recent years, including heart sound denoising, segmentation, feature extraction, and classification recognition. The classification and recognition technologies related to deep learning are presented in detail, with a focus on the application and development of convolutional neural network and recurrent neural network, as well as various combination models for heart sound classification in the past five years.

Authors and Affiliations

Weifeng Wu, Yongqian Zhang, Qianfeng Xu, Jiuzhou Zhao, Rongguo Yan

Keywords

Related Articles

Dipstick color recognition in dry chemical urinalysis: A mini review

Urinalysis is an essential diagnostic tool for urinary tract infections, kidney disease, diabetes, and other clinical conditions. Dipsticks, which allow for quick screening of urine specimens, are used in the clinic sett...

Construction and comparative analysis of an early screening prediction model for fatty liver in elderly patients based on machine learning

Objective: To construct a prediction model for fatty liver disease (FLD) among elderly residents in community using machine learning (ML) algorithms and evaluate its effectiveness. Methods: The physical examination data...

A review of medical image-based diagnosis of COVID-19

The pandemic virus COVID-19 has caused hundreds of millions of infections and deaths, resulting in enormous social and economic losses worldwide. As the virus strains continue to evolve, their ability to spread increases...

The application of mammography imaging in the diagnosis and prediction of breast diseases

Breast diseases pose a significant threat to women's health, so early detection and treatment are extremely important. In this context, early disease identification has become crucial in the diagnosis and treatment of br...

Research progress and clinical application of cooled radiofrequency ablation

Radiofrequency ablation (RFA) is a minimally invasive clinical treatment that uses radiofrequency energy to generate heat, resulting in the thermal necrosis of targeted tissues. To enhance the therapeutic benefits of tra...

Download PDF file
  • EP ID EP750298
  • DOI 10.61189/473511cbaive
  • Views 2
  • Downloads 0

How To Cite

Weifeng Wu, Yongqian Zhang, Qianfeng Xu, Jiuzhou Zhao, Rongguo Yan (2023). Research process on deep learning methods for heart sounds classification. Progress in Medical Devices, 1(2), -. https://europub.co.uk/articles/-A-750298