@Radiology_AI

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. To automatically identify a cohort of patients with pancreatic cystic lesions (PCLs) and to extract PCL measurements from historical computed tomographic (CT) and magnetic resonance (MR) imaging reports using natural language processing (NLP) and a question answering system. Institutional review board approval was obtained for this retrospective HIPAA-compliant study and the requirement to obtain informed consent was waived.