Online service for brain cancer detection and its types prediction using support vector machine with enhanced naive Bayes classifier Online publication date: Sun, 18-Jan-2015
by A.R. Kavitha; C. Chellamuthu
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 17, No. 1, 2015
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.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biomedical Engineering and Technology (IJBET):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook