Fuzzy Rule Based Diagnostic System to Detect the Lung Cancer

Lung cancer is a foreseeable cause for the death of human beings as millions of people are suffering from this disease. Therefore, there is not only need for a system which is capable of detecting and diagnosing cancer but also detects it in its earlier stages so that it can be accurately and properly controlled. A variety of lung cancer detection systems has been developed but there is still a need for improved systems capable of producing effective results. This paper presents such a system which not only encompasses improved diagnosing procedure but also capable to prescribe treatment for lung cancer. The system has nine input parameters and two output parameters. The input and output parameters explain the level or stage of cancer and suggest how to diagnose cancer, at that stage. The parameters are defined based on common signs and symptoms that are often observed while medically examining the patient. A proposed method for designing the system is Mamdani type FIS (fuzzy inference system). In addition, the major parameter which can be a key factor is the time duration which is a crucial consideration in the effective detection and control of the lung cancer at the initial stage.