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Teaching AI for Radiology Applications: a Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM

Title:	Teaching AI for Radiology Applications: a Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM
Authors:	Kitamura, Felipe^{Aff1, Aff2, Aff3}; Kline, Timothy^{Aff1, Aff4}; Warren, Daniel^Aff5; Moy, Linda^Aff6; Daneshjou, Roxana^Aff7; Maleki, Farhad^Aff8; Santos, Igor^Aff9; Gichoya, Judy^Aff10; Wiggins, Walter^{Aff11, Aff12}; Bialecki, Brian^Aff13; O’Donnell, Kevin^Aff14; Flanders, Adam E.^Aff15; Morgan, Matt^Aff16; Safdar, Nabile^{Aff1, Aff10}; Andriole, Katherine P.^Aff17; Geis, Raym^{Aff18, Aff19}; Allen, Bibb^{Aff20, Aff21}; Dreyer, Keith^{Aff21, Aff22}; Lungren, Matt^{Aff23, Aff24, Aff25}; Wood, Monica J.^Aff26; Kohli, Marc^Aff23; Langer, Steve^{Aff1, Aff4}; Shih, George^Aff27; Farina, Eduardo^{Aff1, Aff3, Aff28}; Kahn, Charles E.^Aff29; Reiser, Ingrid^Aff30; Giger, Maryellen^Aff30; Wald, Christoph^{Aff4, Aff13}; Mongan, John^{Aff23, Aff31}; Cook, Tessa^Aff29; Tenenholtz, Neil^{Aff1, Aff21, Aff32, IDs10278025014858_cor1}
Source:	Journal of Imaging Informatics in Medicine. :1-9
Database:	Springer Nature Journals