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Risk analysis in cancer disease by using fuzzy logic

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3 Author(s)
Yilmaz, A. ; Dept. of Comput. Eng., Halic Univ., Istanbul, Turkey ; Ayan, K. ; Adak, E.

Thousands of people die every year because of cancer due to limitation of medical sources and unable to use the existing sources effectively. Loss of patients can be reduced by using the numerical (quantitative) techniques in the system of Medical and Health. Cancer is a genetic disease which is developed by the abnormal cell increase and cell growth as a result of DNA damage and cells being out of the Program. The earlier cancer is diagnosed, so the treatment would be that successful. In this study, the risks of getting cancer for selected pilot people will be discovered by applying the mamdani Fuzzy Logic Model and suggestions will be submitted to the persons to eliminate these risks. In order to resolve the problem, the available figures have been evaluated; leading method and sample have been presented together with fuzzy logic model as a new modality. The reason for selection of fuzzy logic model in this study is that the system uses fuzzy logic model enables to provide effective results depending on uncertain verbal knowledge just like logic of human being. When received good results from the study; our system will make a prediagnosis for the people who possibly can have risk of getting cancer due to working conditions or living standards therefore; this will enable these people to take precautions to the risk of cancer. Besides, the contribution of fuzzy logic model in the field of health and topics of artificial intelligence will also be examined in this study.

Published in:

Fuzzy Information Processing Society (NAFIPS), 2011 Annual Meeting of the North American

Date of Conference:

18-20 March 2011