Automation of Blood Cancer Risk Analysis Using Fuzzy Logic

Abstract

The statistical estimation of the cancer research center shows that approximate 23 million new cases were recorded in 2010 in all over the world. Blood cancer is a deadly disease and have different categories. Symptom of every category is different, but some initial symptoms are same. Research and statistics show that in the majority of cases, people know about the disease when it became too late. Fuzzy is being used in plentiful field like engineering, data mining, medical, science and Computational computing. This research work proposes a method which can be able to assist the doctor in diagnosis of blood Cancer. Fuzzy introduce varies inference but famous fuzzy inference types are Mamdani and TSK. In this article Mamdani Inference System has been proposed to measure the Blood Cancer Detector (BCD). The proposed method Fuzzy Logic based Blood Cancer Detector (BCD) is taking 10 input parameters and 1 output variable. The input variables are BI (Blood Infection), Bleeding, Pains, SC (skin changes), AD (Abdominal Discomforts), VP (Vision problem), WL (weight loss), BP (Bladder problems), fatigue & TP (throat problems), and output variable is BCD.