Tam MDBS, Dyer T, Dissez G, et al. - This study was attempted to assess the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to elevate the accuracy and effectiveness of lung cancer diagnosis by flagging positive cases before passing the remaining examinations to standard reporting. Researchers enrolled a dataset of 400 CXRs including 200 difficult lung cancer cases. The data showed that the proposed AI implementation pathway stands to decrease radiologist errors and improve clinician reporting performance. Moreover, taking a radiologist-centric method in the establishment of clinical AI holds promise for catching systematically missed lung cancers. For lung cancer diagnosis, this represents a tremendous opportunity to improve patient outcomes.