• Dr.K.Padmavathi
• Ms.C.Deepa

Oral Cancer is a considered as complex and wide spread cancer as it is rapidly evolving with a low median survival rate. Currently, duration and cost of the treatment process is long and very high due to its high recurrence and mortality rates. Accurate early diagnosis and prognosis prediction of cancer are become more essential to enhance the patient’s survival rate using medical oncology. Using advanced technologies and machine learning techniques early detection of the deadly disease are made possible. Enabling automated detection and classification of the malignant lesions along computing the prognosis of the disease can be carried out using machine learning techniques with low cost and early diagnosis of the disease. In this paper, experimental study on machine learning technique for oral cancer classification has been carried on basis of defining the disease, diagnosis of the disease, classification of the disease in terms of stages of the lesion on basis of structure and finally prognosis and survival rate. Machine learning model is capable of learning the complex lesion patterns of the disease extracted from feature extraction and feature selection model. Classification of the patterns has been represented into stages. Classification results are highly discriminant with enhanced classification rate on the dynamic characteristics of the images. Evaluation of the technique is estimated using various datasets. The evaluation of the classification technique is based on the feature extraction and feature selection methods. Finally the performance analysis has done with respect to classification accuracy and execution time and attains the effective results on the cross fold validation of the dataset using confusion matrix on basis of precision, recall and f measure.

Machine Learning, Oral Cancer, Classification, Staging, Feature Selection, Feature Extraction

"AN EXPERIMENTAL STUDY ON THE MACHINE LEARNING TECHNIQUES FOR ORAL CANCER CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 8, page no.f173-f176, August-2023, Available :http://www.jetir.org/papers/JETIR2308518.pdf

"AN EXPERIMENTAL STUDY ON THE MACHINE LEARNING TECHNIQUES FOR ORAL CANCER CLASSIFICATION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 8, page no. ppf173-f176, August-2023, Available at : http://www.jetir.org/papers/JETIR2308518.pdf