NDLI: An Intelligent Phonocardiography for Automated Screening of Pediatric Heart Diseases

Content Provider	Springer Nature Link
Author	Sepehri, Amir A. Kocharian, Armen Janani, Azin Gharehbaghi, Arash
Copyright Year	2015
Abstract	This paper presents a robust device for automated screening of pediatric heart diseases based on our unique processing method in murmur characterization; the Arash-Band method. The present study modifies the Arash-Band method and employs output of the modified method in conjunction with the two other original techniques to extract indicative feature vectors for the screening. The extracted feature vectors are classified by using the support vector machine method. Results show that the proposed modifications significantly enhances performance of the Arash-Band in terms of the both accuracy and sensitivity as the corresponding effect sizes are sufficiently large. The proposed algorithm has been incorporated into an Android-based tablet to constitute an intelligent phonocardiogram with the automatic screening capability. In order to obtain confidence interval of the accuracy and sensitivity, an inferable statistical test is applied on our database containing the phonocardiogram signals recorded from 263 of the referrals to a hospital. The expected value of the accuracy/sensitivity is estimated to be 87.45 % / 87.29 % with a 95 % confidence interval of (80.19 % – 92.47 %) / (76.01 % – 95.78 %) exhibiting superior performance than a pediatric cardiologist who relies on conventional or even computer-assisted auscultation.
Starting Page	1
Ending Page	10
Page Count	10
File Format	PDF
ISSN	01485598
Journal	Journal of Medical Systems
Volume Number	40
Issue Number	1
e-ISSN	1573689X
Language	English
Publisher	Springer US
Publisher Date	2015-10-30
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Pediatric heart diseases Intelligent phonocardiogram Phonocardiogram Heart sound Heart murmur Health Informatics Statistics for Life Sciences, Medicine, Health Sciences
Content Type	Text
Resource Type	Article
Subject	Health Information Management Information Systems Health Informatics

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