Extracting Significant Patterns for Oral Cancer Detection Using Apriori Algorithm

Abstract

Presently, no effective tool exists for early\rdiagnosis and treatment of oral cancer. Here, we describe an approach for\rcancer detection and prevention based on analysis using association rule\rmining. The data analyzed are pertaining to clinical symptoms, history of\raddiction, co-morbid condition and survivability of the cancer patients. The\rextracted rules are useful in taking clinical judgments and making right\rdecisions related to the disease. The results shown here are promising and show\rthe potential use of this approach toward eventual development of diagnostic\rassay and treatment with sufficient support and confidence suitable for\rdetection of early-stage oral cancer.