Main Article Content
Since ever, various types of cancer have spread throughout the world. Among the most prominent of these diseases is lung cancer. Many risk factors that cause this disease, such as social, demographic, environmental, behavioral, and medical factors that have claimed the lives of millions of people around the world. Risk factors have a significant impact on the increased number of deaths for people with lung cancer. Various risk factors were identified as criteria in this study according to the literature. The aim of the study is to prioritize lung cancer risk factors for different patient cases through the application of decision support techniques. Multi-criteria decision-making (MCDM) techniques have been adapted to solve decision-making problems in this study. The methodology of study is formed in two steps; 1) calculation the weights of criteria using fuzzy logic integrated with the analytical hierarchy process namely (FAHP) method relied on the pairwise approach; 2) selection the best and worst cases of patient with lung cancer by applying grey relational analysis (GRA)method based on the multiple risk factors. The findings obtained from selecting the best patient (P37), while the worst of patient determined at (P27). Hence, this study might assist physicians in taking appropriate actionaiming to reduce the number of deaths due to lung cancer.