Predicting oral squamous cell carcinoma in tobacco users by utilising fuzzy-based decision tree algorithm Online publication date: Wed, 30-Sep-2020
by Vasantha Kavitha; M. Hanumanthappa
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 12, No. 5, 2020
Abstract: Oral squamous cell carcinoma (OSCC) is one of the major types of malignant and its significant percentage is responsible for the common causes of death worldwide. Many people in India have the habit of smoking tobacco and consumption of alcohol which finally leads to OSCC. Diagnosis, prediction and control of the OSCC are traditionally based on the clinical signs, historical highlights and biomarkers. In dental hospital, the patient may feel inconvenient for the diagnosis on the whole ordinary methods like physical exams. The patients need differential diagnosis biopsy to predict the oral squamous cell carcinoma. In our research, our primary goal is to predict the OSCC from the efficient decision making methods to predict the cancer from the hybrid algorithm; fuzzy-based decision tree algorithm. The entire process is experimented in Hadoop framework with the mapreduce programming model. The proposed system achieves 90% accuracy in the predictions of the oral cancer.
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 Medical Engineering and Informatics (IJMEI):
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