The abstract presents the performances and subpopulation analysis of a computer-aided detection and characterization (CADe/CADx) AI model developed to aid lung cancer screening standard of care. AI 3D-CNN models were used on a test set containing 136 cancer and 2,027 benign patients. Performance at nodule level in terms of AUC-ROC is 0.987, significantly outperforming the NLST Brock model (AUC-ROC 0.971). This result is also consistent across nodules’ key characteristics (size, attenuation, margin) and shows it could aid clinicians in optimizing their clinical routine and the clinical management of patients.