An Intelligent Phonocardiography for Automated Screening of Pediatric Heart Diseases.
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 othe...
| Publicado en: | Journal of Medical Systems Vol. 40; no. 1; pp. 1 - 11 |
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| Autores principales: | , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jan2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115925224&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115925224 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Jan2016 vid: 40 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115925224 115925224 115925224 10.1007/s10916-015-0359-3 115925224 ppf: 1 ppct: 10 formats: fmt: @attributes: type: P tig: atl: An Intelligent Phonocardiography for Automated Screening of Pediatric Heart Diseases. aug: au: Sepehri, Amir Kocharian, Armen Janani, Azin Gharehbaghi, Arash affil: CAPIS Biomedical Research and Development Department, Mons Belgium sug: subj: Automation Pediatric Care Heart Diseases Diagnosis Health Screening Heart Auscultation Artificial Intelligence Descriptive Statistics Confidence Intervals Validity Sensitivity and Specificity Heart Murmurs Diagnosis Human Iran Infant Child, Preschool Child Adolescence Algorithms Heart Diseases Classification Heart Defects, Congenital Classification Pearson's Correlation Coefficient Wilcoxon Signed Rank Test P-Value Data Analysis Software Funding Source Infant: 1-23 months Child, Preschool: 2-5 years Child: 6-12 years Adolescent: 13-18 years ab: 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. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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