This study aimed to assess the use of automated coronary artery calcium (CAC) and quantitative emphysema (percentage of low attenuation areas [%LAA]) in predicting mortality and lung cancer incidence in lung cancer screening. Additionally, the study explored the correlations between %LAA, CAC, and forced expiratory value in 1 second (FEV1). The low-dose computed tomography (LDCT) images were analyzed using fully automated AI software, AVIEW, developed by Coreline Soft. A total of 4098 volunteers were enrolled, and the results showed that %LAA and CAC independently predicted 6-year all-cause, noncancer, and cardiovascular mortality. However, no significant association with lung cancer incidence was found after adjustments. Both biomarkers negatively correlated with FEV1, and %LAA demonstrated moderate discriminative ability in identifying airflow obstruction.