Lung cancer is the common malignant tumor in China

and its incidence and mortality rank first. Due to atypical early symptoms and lack of effective screening methods

most lung cancer patients are detected at an advanced stage and often lead to poor prognosis. The key factors for improving the prognosis of lung cancer patients are early detection

early diagnosis and early treatment. With the continuous progress of cutting-edge technologies such as artificial intelligence and medical big data analysis

Deep learning

as a major branch of artificial intelligence

is recognized as a valuable tool in the field of medical image analysis

and has been widely used in the screening and diagnosis of early-stage lung cancer

treatment decision-making

prediction of prognosis and follow-up of advanced lung cancer

and many results have been reported in previous literatures. This paper reviewed the development status of deep learning technology in the diagnosis and treatment of lung cancer 18 F-FDG PET/CT in recent years

covered the aspects of image acquisition and reconstruction

lesion detection and segmentation

diagnosis and differential diagnosis

gene mutation status and molecular therapeutic target prediction

treatment response and outcome prediction

and analyzed its development prospects and challenges.