A belief rule based expert system to assess Lung Cancer under uncertainty

Lung Cancer which is also known as carcinoma of the lung or pulmonary carcinoma is one kind of fatal lung tumor described by uncontrolled cell growth in the lung tissues. If this tumor left untreated this growth will be spread beyond the lung in the process of metastasis into the nearby tissues or any other parts or organs of the body. Worldwide Lung Cancer is considered as one of the most leading cause of cancer related death in the present time. So, the assessment of lung cancer is a crucial issue. Lung cancer is generally assessed from its signs, symptoms and risk factors by the physicians. However, assessing lung cancer is complex due to the presence of various types of uncertainties such as vagueness, ignorance, imprecision, incompleteness associated with these signs, symptoms and risk factors. The recently developed generic belief rule-based inference methodology by using the evidential reasoning approach (RIMER) has been considered to develop an expert system to assess this disease. The system can deal with various types of uncertainties found in the clinical signs, symptoms and risk factors. The knowledge base of this system has been constructed by taking account of the real patient data as well as with the consultation of the specialists. The practical case studies are provided to test this system. It has been observed that the proposed system is more reliable than from manual system as well as than from fuzzy rule based expert system.