Abstract: Objective To explore the value of an artificial intelligence-based cytopathological diagnostic system in the diagnosis of lung cancer. Methods A total of 101 specimens from patients with pathologically diagnosed as lung cancer in Chinese PLA General Hospital from March to May in 2019 were collected,including 94 lung biopsy specimens,6 pleural fluid specimens and 1 ascites specimen.Of the 101 cases,there were 79 males and 22 females with an average age of 57±10.5 years old.All specimens were smeared and stained,then the artificial intelligence cytopathological diagnostic system and rapid on-site evaluation were applied.The results were compared with the gold standard of pathological diagnosis. Results Totally 101 eligible samples were analyzed.The results showed that the consistency rate between the artificial pathological diagnosis and the gold standard of pathological diagnosis was 66.3%,with sensitivity of 67% and specificity of 60% （χ²=18.380,P=0.000）.The consistency rate of ROSE group and the pathological diagnosis was 64.4%,with sensitivity of 63.7% and specificity of 70% （χ²=15.630,P=0.000）.The consisitency between ROSE and the artificial intelligence cytopathological diagnosis was high. Conclusion The artificial intelligence cytopathological diagnostic system can achieve the equal diagnostic performance of ROSE,which can effectively reduce the workload of medical staff for pathological examination and improve the work efficiency,which has a certain application value in the field of lung cancer diagnosis.