A Semi-automated Fuzzy Multi-criteria Decision Support System for Radiological Diagnosis of Lung Cancer

Abstract

Lung cancer diagnosis is still a challenge because of the subjective differences among experts’ opinions. While the patho-biological basis of lung lesion varies, it becomes imperative to take into consideration every diagnostic modality (macro and microscopic), but usually decision making follows a heuristic framework. A semi-automated fuzzy multi-criteria decision support system is proposed which considers the smeared knowledgebase (embedding heuristics) to understand the problem and adopts a systemic approach to understand lung cancer by malignant potentiality indexing (MPI) and score prediction. Our proposed technique is able to assist for acquisition of information from the experts, analysis of the information, detection of disease potentiality, diagnosis and prognosis through MPI and it may act as an input for patient’s pathological assessment and treatment modality.