NDLI: Fused Hierarchical Neural Networks for Cardiovascular Disease Diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Sekar, B.D. Ming Chui Dong Jun Shi Xiang Yang Hu
Copyright Year	2001
Abstract	A fused hierarchical neural networks (FHNNs) is proposed for applications mainly related to diagnosis and fault detection. The benefit of such a model is well demonstrated by applying FHNNs for cardiovascular disease (CVD) diagnosis hierarchically using hemodynamic parameters (HDPs) derived from non-invasive sphygmogram (SPG). Patients' medical records with diagnostic results confirmed by doctors obtained from two hospitals in China are used to test and verify FHNNs. Variance analysis is used to categorize HDPs according to the importance/relevance based on their influence on discriminating diseases. Different neural networks structures are tested in diagnosing CVD so as to choose the optimal sub neural networks (sub-NNs) for the proposed FHNNs. Finally FHNNs with fused sub-NNs for CVD diagnosis is presented. The validity and effectiveness in the improvement of accuracy is witnessed clearly from the testing results.
Sponsorship	IEEE Sensors Council
Starting Page	644
Ending Page	650
Page Count	7
File Size	710705
File Format	PDF
ISSN	1530437X
Volume Number	12
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Artificial neural networks Training Medical diagnostic imaging Testing Hospitals variance analysis Cardiovascular disease (CVD) fuzzy probabilistic neural networks (FPNNs) fuzzy learning vector quantization hierarchical neural networks (HNNs)
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

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

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