Web based fuzzy expert system for lung cancer diagnosis

Abstract

Currently, cancer is a leading cause of death worldwide. One of the most common causes of cancer death are lung cancer. We implemented a lung cancer detection using Sugeno Fuzzy Logic method. We use PHP to construct a website based of an expert system and MySQL for our database collection. The source of our data used to build the expert system are collected from many literature studies related to medical books and interviews with the doctors or physicians to assemble 5 different variables that we use as input. The variables are anamnesis, doubling time, the degree of the smokers, age and performance status. The result of expert system's diagnoses produce three assumptions, (i) no tumor is indicated, (ii) tumor is indicated but benign and (iii) malignant tumors are indicated. The designs of this system are expected to help doctors and physicians to aid them in making a diagnosis of lung cancer.