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Radiology|November 21, 2017
When Machines Think: Radiology's Next FrontierKeith J Dreyer, J Raymond GeisJournal of the American College of Radiology : JACR|April 6, 2015
The imaging 3.0 informatics scorecardMarc Kohli, Keith J Dreyer, J Raymond GeisAJR. American Journal of Roentgenology|March 21, 2015
Rethinking radiology informaticsMarc Kohli, Keith J Dreyer, J Raymond GeisRadiology|June 27, 2018
Current Applications and Future Impact of Machine Learning in RadiologyGarry Choy, Omid Khalilzadeh, Mark Michalski, et al.Journal of the American College of Radiology : JACR|February 25, 2017
Meaningful Peer Review in Radiology: A Review of Current Practices and Potential Future DirectionsAndrew K Moriarity, C Matthew Hawkins, J Raymond Geis, et al.Journal of the American College of Radiology : JACR|November 22, 2017
Machine Learning in Radiology: Applications Beyond Image InterpretationParas Lakhani, Adam B Prater, R Kent Hutson, et al.Journal of Digital Imaging|May 19, 2017
Medical Image Data and Datasets in the Era of Machine Learning-Whitepaper from the 2016 C-MIMI Meeting Dataset SessionMarc D Kohli, Ronald M Summers, J Raymond GeisJournal of the American College of Radiology : JACR|December 4, 2014
IT infrastructure in the era of imaging 3.0Geraldine B McGinty, Bibb Allen, J Raymond Geis, et al.Academic Radiology|June 5, 2025
Regulating Generative AI in Radiology Practice: A Trilaminar Approach to Balancing Risk with InnovationVrushab Gowda, Bernardo C Bizzo, Keith J DreyerAJR. American Journal of Roentgenology|January 27, 2017
Implementing Machine Learning in Radiology Practice and ResearchMarc Kohli, Luciano M Prevedello, Ross W Filice, et al.Pageof 7