An Intelligent Diagnostic System for Congenital Heart Defects

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An Intelligent Diagnostic System for Congenital Heart Defects

Journal Title: International Journal of Advanced Computer Science & Applications - Year 2013, Vol 4, Issue 7

Abstract

Congenital heart disease is the most common birth defect. The article describes detection and classification of congenital heart defect using classification and regressing trees. The ultimate goal of this research can decrease risk of cardiac arrest and mortality in compared with healthy children. The intelligent system proposed in three stages technique for automate diagnosis:(i) pre-processing(ii), feature extraction, and (iii) classification of congenital heart defects (CHD) using data mining tools. The intelligent diagnostic system has been validated with a representative dataset of 110 heart sound signals, taken from healthy and unhealthy medical cases. This system was evaluated in the test dataset with the following performance measurements global accuracy: 98.18%, sensitivity, 96.36% and specificity 100%. This results show the feasibility of classification based on optimized feature extraction and classifier. This paper follows the Association for the recommendations of the Advancement of Medical Instrumentation.

Authors and Affiliations

Amir Amiri, Giuliano Armano

Keywords

congenital heart defects Heart Murmurs newborn classification and regression trees;

EP ID EP161877
DOI 10.14569/IJACSA.2013.040714
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