Early Diagnosis in Cancer Disease by Using Fuzzy Logic and the Effects of Stress on Cancer

International Review on Computers and Software, vol.6, no.3, pp.347-354, 2011 (Peer-Reviewed Journal)

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. The earlier

cancer is diagnosed, so the treatment would be that successful. In this study risk of getting lung

cancer of people are going to be deduced and the opportunity to destroy this risk will be able to be

suggested to the patient. Affects of stress to cancer are going to be examined after evaluating the

risk value of cancer is going to be evaluated in the basis of self resistance of the person to cancer

expect of risk result and aptitude to stress. 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 pre-diagnosis 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.