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Radiology|October 21, 2025
AI for Radiology: A Primer Part I. From Idea to AlgorithmAli S Tejani, Andreas M Rauschecker, Marc Kohli, et al.
Radiology. Artificial Intelligence|October 7, 2021
RSNA-MICCAI Panel Discussion: Machine Learning for Radiology from Challenges to Clinical ApplicationsJohn Mongan, Jayashree Kalpathy-Cramer, Adam Flanders, et al.
Radiographics : a Review Publication of the Radiological Society of North America, Inc|September 13, 2017
Correlate: A PACS- and EHR-integrated Tool Leveraging Natural Language Processing to Provide Automated Clinical Follow-upMark D Kovacs, Joseph Mesterhazy, David Avrin, et al.
Journal of Digital Imaging|October 13, 2016
High-Throughput Classification of Radiographs Using Deep Convolutional Neural NetworksAlvin Rajkomar, Sneha Lingam, Andrew G Taylor, et al.
Journal of Chemical Theory and Computation|November 13, 2010
Generalized Born model with a simple, robust molecular volume correctionJohn Mongan, Carlos Simmerling, J Andrew McCammon, et al.
Journal of Endourology|November 5, 2016
Feasibility of Retrograde Ureteral Contrast Injection to Guide Ultrasonographic Percutaneous Renal Access in the Nondilated Collecting SystemManint Usawachintachit, David T Tzou, John Mongan, et al.
Journal of the American Chemical Society|October 13, 2005
Potent, selective pyrone-based inhibitors of stromelysin-1David T Puerta, John Mongan, Ba L Tran, et al.
AJR. American Journal of Roentgenology|July 25, 2012
Pancreatic imaging mimics: part 1, imaging mimics of pancreatic adenocarcinomaFergus V Coakley, Katryana Hanley-Knutson, John Mongan, et al.
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