Title: Predicting oral squamous cell carcinoma in tobacco users by utilising fuzzy-based decision tree algorithm

Authors: Vasantha Kavitha; M. Hanumanthappa

Addresses: Department of Computer Science, Bharathiar University, Coimbatore, India ' Department of Computer Science and Applications, Bangalore University, Bangalore, India

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.

Keywords: oral squamous cell carcinoma; OSCC; decision tree; fuzzy logic; Hadoop; mapreduce programming; classification.

DOI: 10.1504/IJMEI.2020.109939

International Journal of Medical Engineering and Informatics, 2020 Vol.12 No.5, pp.435 - 446

Received: 08 Jan 2018
Accepted: 11 Sep 2018
Published online: 30 Sep 2020 *

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