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Detection of Oral Cancer Using Machine Learning Classification Methods

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Document pages: 10 pages

Abstract: Oral cancer is one of the most dangerous cancers which affects and originates from the oral cavity and neck. Overuse of tobacco and smoking cigarettes are the primary risk factor for developing oral cancer. This technique derives a group of features that would help the classifiers to identify the image state automatically. Various machine learning methods are applied on the datasets and their performance are analyzed. The derived features were classified using CNN, which are compared against various standard classification approaches such as SVM, Naive bayes. From the results, it is observed that the different stage classification of oral cancer can be classified effectively. Hence, the classification of various oral cancers can be achieved more efficiently by means of CNN.

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