Lung cancer is the leading cause of cancer death worldwide. Effective screening and early detection are critical in reducing mortality. Artificial intelligence (AI) methods have been proved useful in the diagnosis of pulmonary nodules and early diagnosis of lung cancer. However, the implementation of lung cancer screening and frequent detection of incidental pulmonary nodules lead to more computed tomography scans resulting in increased costs. Therefore, determining the cost-effectiveness of AI …