Abstract: Early detection and accurate diagnosis are critical for the prognosis of lung cancer. Radiological imaging could reflect tumor heterogeneity in a non-invasive and comprehensive manner. Deep mining of high throughput imaging data is a big challenge for radiologists. Artificial intelligence (AI) methods excel at processing large quantities of high-dimensional information and analyzing data using algorithm. It can automatically recognize complex patterns in imaging data, provide quantitative assessments of radiographic characteristics, and is promising in tumor detection and diagnosis. Precision medicine could be made when AI was integrated into the clinical workflow as a tool to assist radiologists. Here we review the current progress and discuss the challenges and future directions of AI applications in lung tumor imaging diagnosis.