• Ramesh
• Dhanalakshmi

Oral squamous cell carcinoma (OSCC) constitutes is one of the major type malignant and its significant percentage of oral squamous cell carcinomas and are one of the most common causes of death worldwide. Diagnosis, prediction and control of the OSCC are practically done traditionally based on the clinical signs and historical highlights and biomarkers. Because of absence of convenient diagnosis on the whole ordinary methods or differential diagnosis biopsy of the patient is required. Therefore the patient may be feel inconvenient and lack of knowledge for the hospital staffs or doctors to predict the cancer. In our research, our primary aim to predict and efficient decision making of cancer and its treatment by the historical patient data set and symptoms like smoking and drinking. We use fuzzy based machine learning algorithm to classify and predict the OSCC. The presented system isexpected to validly improve the healthcare services by considering the methods.

OSCC , Oral Cancer, Decision Making, biopsy

"An Efficient Decision making of oral cancer Using fuzzy based machine learning algorithm in Hadoop Framework", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.731-737, August-2018, Available :http://www.jetir.org/papers/JETIR1808747.pdf

"An Efficient Decision making of oral cancer Using fuzzy based machine learning algorithm in Hadoop Framework", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp731-737, August-2018, Available at : http://www.jetir.org/papers/JETIR1808747.pdf