Presently, no effective tool exists for early diagnosis and treatment of oral cancer. Here, we describe an approach for cancer detection and prevention based on analysis using association rule mining. The data analyzed are pertaining to clinical symptoms, history of addiction, co-morbid condition and survivability of the cancer patients. The extracted rules are useful in taking clinical judgments and making right decisions related to the disease. The results shown here are promising and show the potential use of this approach toward eventual development of diagnostic assay and treatment with sufficient support and confidence suitable for detection of early-stage oral cancer.
Fayyad, U. M., Piatetsky-Shapiro, G. and Smyth, P. (1996) Data Mining to Knowledge Discovery in Databases. AI Magazine, 17, 37-54.
Han, J., Kamber, M. and Pei, J. (2011) Data Mining: Concepts and Techniques. 3rd Edison, Morgan Kaufmann Publishers, Burlington.
Khosla, R. and Dillon, T. (1997) Knowledge Discovery, Data Mining and Hybrid Systems. Engineering Intelligent Hybrid Multi-Agent Systems, Kluwer Academic Publishers, Norwell, 143-177.
Kincade, K. (1998) Data Mining: Digging for Healthcare Gold. Insurance & Technology, 23, IM2-IM7.
Milley, A. (2000) Healthcare and Data Mining. Health Management Technology, 21, 44-47.
Fayyad, U.M., Piatetsky-Shapiro, G. and Smyth, P. (1996) Data Mining to Knowledge Discovery: An Overview. Advances in Knowledge Discovery and Data Mining, AAAI Press/MIT Press, 1-36.
Houston, A.L., Chen, H., Hubbard, S.M., Schatz, B.R. , Ng, T.D., Sewell, R.R. and Tolle, K.M. (1999) Medical Data Mining on the Internet: Research on a Cancer Information System. Artificial Intelligence Review, 13, 437-466. http://dx.doi.org/10.1023/A:1006548623067
Koh, H.C. and Tan, G. (2005) Data Mining Applications in Healthcare. Journal of Healthcare Information Management, 19, 64-72.
Cios, K.J. (2001) Medical Data Mining and Knowledge Discovery. Studies in Fuzziness and Soft Computing, 60, 502.
Mathers, C.D. and Loncar, D. (2006) Projections of Global Mortality and Burden of Disease. PLOS Medicine, 3, 2002-2030.
World Health Organization (2007) Department of Measurement and Health Information Systems: World Health Statistics 2007, World Health Organization, Geneva.
World Health Organization (2002) Department of Management of Noncommunicable Diseases: National Cancer Control Programmes, World Health Organization, Geneva.
Kaladhar, D.S.V.G.K., Chandana, B. and Kumar, P.B. (2011) Predicting Cancer Survivability Using Classification Algorithms. International Journal of Research and Reviews in Computer Science (IJRRCS), 2, 340-343.
Singh, S., Yadav, M. and Gupta, H. (2012) Finding the Chances and Prediction of Cancer through Apriori Algorithm with Transaction Reduction. International Journal of Advanced Computer Research, 2, 23-28.
Srikant, R., Vu, Q. and Agrawal, R. (1997) Mining Association Rules with Item Constraints. Proceeding KDD9, New Port Beach, 14-17 August 1997, 67-73.
Nahar, J., Kevin, S.T., Ali, A.B.M.S. and Chen, Y.P. (2009) Significant Cancer Prevention Factor Extraction: An Association Rule Discovery Approach. Journal of Medical Systems, 35, 353-367. DOI 10.1007/s10916-009-9372-8
Swami, S., Thakur, R.S. and Chandel, R.S. (2011) Multi-Dimensional Association Rules Extraction in Smoking Habits Database. International Journal of Advanced Networking and Applications, 3, 1176-1179.
Milovic, B. and Milovic, M. (2012) Prediction and Decision Making in Health Care Using Data Mining. International Journal of Public Health Science, 1, 69-78.
Anuradha, K. and Sankaranarayanan, K. (2012) Identification of Suspicious Regions to Detect Oral Cancers at an Earlier Stage—A Literature SURVEY. International Journal of Advances in Engineering & Technology, 3, 84-91.
Chuang, L.Y., Wu, K.C., Chang, H.W. and Yang, C.H. (2011) Support Vector Machine-Based Prediction for Oral Cancer Using Four SNPs in DNA Repair Genes. Proceedings of the International Multi Conference of Engineers and Computer Scientists, Hong Kong,16-18 March 2011, 16-18.
Gadewal, N.S. and Zingde, S.M. (2011) Database and Interaction Network of Genes Involved in Oral Cancer: Version II. Bioinformation, 6, 169-170. http://dx.doi.org/10.6026/97320630006169
Perkin, D.M. and Lara, E. (1980) Estimates of the World Wide Frequency of Sixteen Major Cancers. International Journal of Cancer, 41, 184-197.
Elango, J.K., Gangadharan, P., Sumithra, S. and Kuriakose, M.A. (2006) Trends of Head and Neck Cancers in Urban And Rural India. Asian Pacific Journal of Cancer Prevention, 7, 108-112.
Sankaranarayan, R., Masuyer, E., Swaminathan, R., Ferley, J. and Whelan, S. (1998) Head and Neck Cancer: A Global Perspective on Epidemiology and Prognosis. Anticancer Research, 18, 4779-4786.
Sankaranarayanan, R., Ramadas, K. and Thomas, K. (2005) Effect of Screening on Oral Cancer Mortality in Kerala, India: A Cluster-Randomised Controlled Trial. The Lancet, 365, 1927-1933. http://dx.doi.org/10.1016/S0140-6736(05)66658-5
Manoharan, N., Tyagi, B.B. and Raina, V. (2004) Cancer incidences in rural Delhi. Asian Pacific Journal of Cancer Prevention, 11, 73-78.
Agrawal, M., Pandey, S., Jain, S. and Maitin, S. (2012) Oral Cancer Awareness of the General Public in Gorakhpur City, India. Asian Pacific Journal of Cancer Prevention, 13, 5195-5199. http://dx.doi.org/10.7314/APJCP.2012.13.10.5195
American Cancer Society (1996) Cancer Facts and figures, Atlanta (GA), The Society.
Cancer Research Capign (1990) Oral Cancer. Fact Sheet, 14.
Agrawal, R., Imielinski, T. and Swami, A. (1993) Mining Association Rules between Sets of Items in Large Databases. Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, Washington DC, May 1993, 207-216.
An, J., Chen, Y.P.P. and Chen, H. (2005) DDR: An Index Method for Large Time Series Datasets. Information Systems, 30, 333-348. http://dx.doi.org/10.1016/j.is.2004.05.001
Chen, Y.P.P. and Chen, F. (2008) Targets for Drug Discovery Using Bioinformatics. Expert Opinion on Therapeutic Targets, 12, 383-389. http://dx.doi.org/10.1517/14728222.12.4.383
Lau, R.Y.K., Tang, M., Wong, O., Milliner, S.W. and Chen, Y.P.P. (2006) An Evolutionary Learning Approach for Adaptive Negotiation Agents. International Journal of Intelligent Systems, 21, 41-72. http://dx.doi.org/10.1002/int.20120
Ordonez, C. (2006) Association Rule Discovery with the Train and Test Approach for Heart Disease Prediction. IEEE Transaction on Information Technology. Biomed, 10, 334-343. http://dx.doi.org/10.1109/TITB.2006.864475
Ordonez, C. and Omiecinski, E. (1999) Discovering Association Rules Based on Image Content. IEEE Advances in Digital Libraries Conference (ADL’99), Baltimore, 19-21 May 1999, 38-49.
Ordonez, C., Santana, C.A. and Braal, L. (2000) Discovering Interesting Association Rules in Medical Data. ACM DMKD Workshop, Dallas, 14 May 2000, 78-85.
Agrawal, R. and Srikant, R. (1994) Fast Algorithms for Mining Association Rules in Large Databases. Proceedings of the 20th International Conference on Very Large Data Bases, VLDB, Santiago de Chile, 12-15 September 1994, 487-499.
Zaki, M.J. (2004) Mining Non-Redundant Association Rules. Data Mining and Knowledge Discovery, 9, 223-248. http://dx.doi.org/10.1023/B:DAMI.0000040429.96086.c7
Agrawal, R., Imielinski, T. and Swami, A. (1993) Mining Association Rules between Sets of Items in Large Databases. Proceedings of the 1993 ACM SIGMOD International Conference on Management of Data, Washington DC, 26-28 May 1993, 207-216.
Hipp, J., Güntzer, U. and Nakhaeizadeh, G. (2000) Algorithms for Association Rule Mining—A General Survey and Comparison. ACM SIGKDD Explorations Newsletter, 2, 58-64. http://dx.doi.org/10.1145/360402.360421
Brin, S., Motwani, R., Ullman, J.D. and Tsur, S. (1997) Dynamic Itemset Counting and Implication Rules for Market Basket Data. Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 1997), Tucson, 13-15 May 1997, 255-264.
Piatetsky-Shapiro, G. (1991) Discovery, Analysis, and Presentation of Strong Rules. Knowledge Discovery in Databases. AAAI/MIT Press, Cambridge, 248, 255-264.
Brin, S., Motwani, R., Ullman, J.D. and Tsur, S. (1997) Dynamic Itemset Counting and Implication Rules for Market Basket Data. Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD 1997), Tucson, 13-15 May 1997, 265-276.
Sharma, N. and Om, H. (2012) Framework for Early Detection and Prevention of Oral Cancer Using Data Mining. International Journal of Advances in Engineering & Technology, 4, 302-310.
Witten, I.H. and Frank, E. (2005) Data Mining: Practical Machine Learning Tool and Techniques. 2nd Edition, Elsevier, Amsterdam.