NDLI: Detection and Classification of Cardiac Murmurs using Segmentation Techniques and Artificial Neural Networks

Content Provider	IEEE Xplore Digital Library
Author	Strunic, S.L. Rios-Gutierrez, F. Alba-Flores, R. Nordehn, G. Burns, S.
Copyright Year	2007
Description	Author affiliation: Minnesota Duluth Univ., MN (Strunic, S.L.; Rios-Gutierrez, F.; Alba-Flores, R.; Nordehn, G.; Burns, S.)
Abstract	In this paper we present the implementation of a diagnostic system based on artificial neural networks (ANN) that can be used in the detection and classification of heart murmurs. Segmentation and alignment algorithms serve as important pre-processing steps before heart sounds are applied to the ANN structure. The system enables users to create a classifier that can be trained to detect virtually any desired target set of heart sounds. The output of the system is the classification of the sound as either normal or a type of heart murmur. The ultimate goal of this research is to implement a heart sounds diagnostic system that can be used to help physicians in the auscultation of patients and to reduce the number of unnecessary echocardiograms - those that are ordered for healthy patients. Testing has been conducted using both simulated and recorded patient heart sounds as input. Three sets of results for the tested system are included herein, corresponding to three different target sets of simulated heart sounds. The system is able to classify with up to 85 plusmn 7.4% accuracy and 95 plusmn 6.8% sensitivity. For each target set, the accuracy rate of the ANN system is compared to the accuracy rate of a group of 2nd year medical students who were asked to classify heart sounds from the same group of heart sounds classified by the ANN system. System test results are also explored using recorded patient heart sounds
Starting Page	397
Ending Page	404
File Size	9371361
Page Count	8
File Format	PDF
ISBN	1424407052
DOI	10.1109/CIDM.2007.368902
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-03-01
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Heart System testing Pathology Acoustic testing Costs Medical simulation Artificial neural networks Medical services Data mining Computational intelligence
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in