This paper proposes a novel method to analyze and classify the cardiovascular ultrasound echocardiographic images using Naïve-Bayesian model via database OLAP-SQL. Efficient data mining algorithms based on tightly-coupled model is used to extract features. Three algorithms are proposed for classification namely Naïve-Bayesian Classifier for Discrete variables (NBCD) with SQL, NBCD with OLAP-SQL, and Naïve-Bayesian Classifier for Continuous variables (NBCC) using OLAP-SQL. The proposed model is trained with 207 patient images containing normal and abnormal categories. Out of the three proposed algorithms, a high classification accuracy of 96.59% was achieved from NBCC which is better than the earlier methods.
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S. Nandagopalan*, Suryanarayana, A. B., Sudarshan, T. S. B., Chandrashekar, D., and Manjunath, C. N., “SQL based cardiovascular ultrasound image classification”, International journal of data mining and bioinformatics, vol. 7, pp. 266–283, 2013.