Adams SJ, Mondal P, Penz E, et al. - This study was intended to help construct a lung nodule management strategy combining the Lung CT Screening Reporting and Data System (Lung-RADS) with an artificial intelligence (AI) malignancy-risk score and ascertain its effect on follow-up investigations and related costs in a baseline lung cancer screening population. For 192 baseline low-dose CT studies, a secondary analysis was done using a data set of AI malignancy risk scores and Lung-RADS classifications from six radiologists. Researchers ascertained Lung-RADS and the AI-informed management strategy. The findings exhibited that fewer follow-up investigations and substantial cost savings may result from lung cancer screening using an AI risk score combined with Lung-RADS at baseline. The AI-informed management strategy achieved sensitivity of 91% and a specificity of 96%.