Results 31 to 40 of about 29,039 (221)

Lightweight End-to-End Neural Network Model for Automatic Heart Sound Classification

Information, 2021
Heart sounds play an important role in the initial screening of heart diseases. However, the accurate diagnosis with heart sound signals requires doctors to have many years of clinical experience and relevant professional knowledge.
Tao Li, Yibo Yin, Kainan Ma, Sitao Zhang, Ming Liu   +4 more
doaj   +1 more source

Conv-Random Forest-Based IoT: A Deep Learning Model Based on CNN and Random Forest for Classification and Analysis of Valvular Heart Diseases

IEEE Open Journal of Instrumentation and Measurement, 2023
Cardiovascular diseases are growing rapidly in this world. Around 70% of the world’s population is suffering from the same. The entire research work is grouped into the classification and analysis of heart sound.
Tanmay Sinha Roy, Joyanta Kumar Roy, Nirupama Mandal   +2 more
doaj   +1 more source

Heart Sound Classification via Sparse Coding

2016 Computing in Cardiology Conference (CinC), 2016
Introduction: The aim of the Physionet/CinC Challenge 2016 is to automatically classify heart sound recordings as normal or abnormal. The Challenge provides 3,153 labeled audio recordings taken from a single precordial location, as well as Springer's state-of-the-art beat segmentation algorithm.
Bradley Whitaker, David Anderson
openaire   +1 more source

Optimal Heart Sound Segmentation Algorithm Based on K-Mean Clustering and Wavelet Transform

Applied Sciences, 2023
The accurate localization of S1 and S2 is essential for heart sound segmentation and classification. However, current direct heart sound segmentation algorithms have poor noise immunity and low accuracy. Therefore, this paper proposes a new optimal heart
Xingchen Xu, Xingguang Geng, Zhixing Gao, Hao Yang, Zhiwei Dai, Haiying Zhang   +5 more
doaj   +1 more source

Design and Application of a Laconic Heart Sound Neural Network

IEEE Access, 2019
To design a classification algorithm of heart sounds with low hardware requirements and applicability to mobile terminals, this paper proposes a laconic heart sound neural network (LHSNN).
Xiefeng Cheng, Jianzhong Huang, Yunyi Li, Guan Gui   +3 more
doaj   +1 more source

Heart Sound Signals Segmentation and Multiclass Classification

International Journal of Online and Biomedical Engineering (iJOE), 2020
The heart is the organ that pumps blood with oxygen and nutrients into all body organs by a rhythmic cycle overlapping between contraction and dilatation. This is done by producing an audible sound which we can hear using a stethoscope. Many are the causes affecting the normal function of this most vital organ.
Abdelhamid Bourouhou, Abdelilah Jilbab, Chafik Nacir, Ahmed Hammouch   +3 more
openaire   +2 more sources

Assistive diagnostic technology for congenital heart disease based on fusion features and deep learning

Frontiers in Physiology, 2023
Introduction: Congenital heart disease (CHD) is a cardiovascular disorder caused by structural defects in the heart. Early screening holds significant importance for the effective treatment of this condition.
Yuanlin Wang, Xuankai Yang, Xiaozhao Qian, Weilian Wang, Tao Guo   +4 more
doaj   +1 more source

Segmentation of Heart Sound Signal Based on Multi-Scale Feature Fusion and Multi-Classification of Congenital Heart Disease

Bioengineering
Analyzing heart sound signals presents a novel approach for early diagnosis of pediatric congenital heart disease. The existing segmentation algorithms have limitations in accurately distinguishing the first (S1) and second (S2) heart sounds, limiting ...
Yuan Zeng, Mingzhe Li, Zhaoming He, Ling Zhou   +3 more
doaj   +1 more source

An automatic segmentation method for heart sounds

BioMedical Engineering OnLine, 2018
Background There are two major challenges in automated heart sound analysis: segmentation and classification. An efficient segmentation is capable of providing valuable diagnostic information of patients.
Qingshu Liu, Xiaomei Wu, Xiaojing Ma
doaj   +1 more source

Exploring composite dataset biases for heart sound classification [PDF]

CEUR Workshop Proceedings, 2020
In the last few years, the automatic classification of heart sounds has been widely studied as a screening method for heart disease. Some of these studies have achieved high accuracies in heart abnormality prediction. However, for such models to assist clinicians in the detection of heart abnormalities, it is of critical importance that they are ...
Shariat Panah, Davoud, Hines, Andrew, McKeever, Susan   +2 more
openaire   +1 more source