Title: Online service for brain cancer detection and its types prediction using support vector machine with enhanced naive Bayes classifier

Authors: A.R. Kavitha; C. Chellamuthu

Addresses: Information Technology Department, Jerusalem College of Engineering, Anna University, Chennai 600100, India ' EEE Department, R.M.K. Engineering College, Anna University, Chennai 600025, India

Abstract: This paper proposes an efficient online service for brain cancer prediction and its type prediction r based on SVM with Enhanced Naive Bayes Classifier (SVMENBC) algorithm. The patient's data set acquired are compiled using the MySql software. A set of questionnaire and precondition patterns are designed using the Eclipse Indigo with MS SQL software, and are maintained in the database. The designed questionnaire is given to the users through the web browser and their response is considered the input pattern. The pattern matching technique matches the input pattern and the precondition patterns. The SVM classifies the data set into brain cancer or cancerous data. Finally, the type of the brain cancer is identified from the brain tumour data set using enhanced naive Bayes classifier. The performance of the proposed SVMENBC is validated both quantitatively and qualitatively using the performance metrics such as sensitivity, specificity and accuracy.

Keywords: brain cancer detection; naive Bayes classifier; XML; internet; web services; cancer type prediction; online services; support vector machines; SVM; precondition patterns; pattern matching; brain tumour datasets.

DOI: 10.1504/IJBET.2015.066968

International Journal of Biomedical Engineering and Technology, 2015 Vol.17 No.1, pp.55 - 71

Received: 21 Jun 2014
Accepted: 15 Sep 2014
Published online: 18 Jan 2015 *

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