A multiple decision tree-based method for differentiation of a split first heart sound from a fourth heart sound and ejection click

Stasis, A; Pavlopoulos, S; Loukis, E

dc.contributor.author	Stasis, A	en
dc.contributor.author	Pavlopoulos, S	en
dc.contributor.author	Loukis, E	en
dc.date.accessioned	2014-03-01T01:53:38Z
dc.date.available	2014-03-01T01:53:38Z
dc.date.issued	2004	en
dc.identifier.issn	1479649X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/27079
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-11344283716&partnerID=40&md5=27e52bae821f14aaeb3f2b70a5a5f759	en
dc.subject.other	aorta coarctation	en
dc.subject.other	aorta stenosis	en
dc.subject.other	aorta valve regurgitation	en
dc.subject.other	article	en
dc.subject.other	auscultation	en
dc.subject.other	computer analysis	en
dc.subject.other	computer assisted diagnosis	en
dc.subject.other	decision support system	en
dc.subject.other	decision theory	en
dc.subject.other	diagnostic accuracy	en
dc.subject.other	differential diagnosis	en
dc.subject.other	disease classification	en
dc.subject.other	Eisenmenger complex	en
dc.subject.other	experience	en
dc.subject.other	heart atrium septum defect	en
dc.subject.other	heart disease	en
dc.subject.other	heart infarction	en
dc.subject.other	heart muscle ischemia	en
dc.subject.other	heart right bundle branch block	en
dc.subject.other	heart sound	en
dc.subject.other	heart ventricle extrasystole	en
dc.subject.other	heart ventricle hypertrophy	en
dc.subject.other	human	en
dc.subject.other	hypertension	en
dc.subject.other	hypertrophic cardiomyopathy	en
dc.subject.other	intermethod comparison	en
dc.subject.other	mitral valve disease	en
dc.subject.other	pulmonary hypertension	en
dc.subject.other	pulmonary valve stenosis	en
dc.subject.other	sensitivity and specificity	en
dc.subject.other	tricuspid valve stenosis	en
dc.title	A multiple decision tree-based method for differentiation of a split first heart sound from a fourth heart sound and ejection click	en
heal.type	journalArticle	en
heal.publicationDate	2004	en
heal.abstract	Objective: Differentiating a fourth heart sound (S4), from a split first heart sound (SP1), or ejection click (EC), is often difficult particularly for inexperienced clinicians. The objective of this study was to develop and evaluate a computer-assisted classification tool to aid in this difficult differentiation problem, and in general for heart sound differentiation and diagnosis. Design: Developmental study. Methods: Emphasis was given to the selection of appropriate features that are adequately independent from the heart sound signal acquisition method. Relevance analysis was initially performed to identify the features of the heart sound most relevant to aiding diagnosis of S4, SP1 and EC. To detect and differentiate S4, SP1 and EC, a detection decision tree (DeDT) and a differentiation decision tree (DiDT) were used independently and also together in a multiple decision tree architecture. The DeDT provides three suggestions for each heart sound pattern, whereas the DOT provides one. The MuDT analyses the suggestions of both decision trees to provide one final suggestion for each sound pattern. Results: Relevance analysis on the different heart sound features demonstrated that the most relevant features for aiding diagnosis of S4, SP1 and EC are the frequency features and the morphological features that describe S1. The DeDT architecture demonstrated an average classification accuracy of 80.56%, sensitivity of 70.93%, and specificity of 83.42%, but provided more than one suggestion for many cases. The DiDT architecture demonstrated an average classification accuracy of 66.46%, a sensitivity of 66.15% and a specificity of 82.15%, and only provided one suggestion for each case. The MuDT architecture slightly improved performance compared to the DiDT architecture. Average classification accuracy was improved by 2.79%, classification sensitivity by 2.73% and classification specificity by 1.26%. Conclusions: The present work has demonstrated that decision tree algorithms can be successfully used as the basis for a decision support system to assist inexperienced clinicians in heart sound diagnosis. Further work is currently in progress to improve the accuracy, specificity and sensitivity of the system. © The Journal on Information Technology in Healthcare 2004.	en
heal.journalName	Journal on Information Technology in Healthcare	en
dc.identifier.volume	2	en
dc.identifier.issue	6	en
dc.identifier.spage	413	en
dc.identifier.epage	426	en