Review of Artificial Intelligence Training Tools and Courses for Radiologists

Michael L Richardson; Scott J Adams; Atul Agarwal; William F Auffermann; Anup K Bhattacharya; Nikita Consul; Joseph S Fotos; Linda C Kelahan; Christine Lin; Hao S Lo; Xuan V Nguyen; Lonie R Salkowski; Jessica M Sin; Robert C Thomas; Shafik Wassef; Ichiro Ikuta

doi:10.1016/j.acra.2020.12.026

Review of Artificial Intelligence Training Tools and Courses for Radiologists

Acad Radiol. 2021 Sep;28(9):1238-1252. doi: 10.1016/j.acra.2020.12.026. Epub 2021 Mar 11.

Authors

Michael L Richardson¹, Scott J Adams², Atul Agarwal³, William F Auffermann⁴, Anup K Bhattacharya⁵, Nikita Consul⁶, Joseph S Fotos⁷, Linda C Kelahan⁸, Christine Lin⁹, Hao S Lo¹⁰, Xuan V Nguyen¹¹, Lonie R Salkowski¹², Jessica M Sin¹³, Robert C Thomas¹⁴, Shafik Wassef¹⁵, Ichiro Ikuta¹⁶

Affiliations

¹ Department of Radiology, University of Washington, Seattle, Washington. Electronic address: mrich@uw.edu.
² Department of Medical Imaging, University of Saskatchewan, Saskatoon, SK, Canada.
³ Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, Indiana.
⁴ Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah.
⁵ Mallinckrodt Institute of Radiology, St. Louis, Missouri.
⁶ Department of Radiology, Baylor College of Medicine, Houston, Texas.
⁷ Department of Radiology, Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania.
⁸ Department of Radiology, Northwestern University, Chicago, Illinois.
⁹ College of Medicine, Penn State Milton S. Hershey Medical Center, Hershey, Pennsylvania.
¹⁰ Department of Radiology, University of Massachusetts, Worcester, Massachusetts.
¹¹ Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio.
¹² Department of Radiology, University of Wisconsin, Madison, Wisconsin.
¹³ Dartmouth Hitchcock Clinics, Lebanon, New Hampshire.
¹⁴ School of Medicine, Louisiana State University, New Orleans, Los Angeles, United States.
¹⁵ Medical Imaging and Interventions Specialists, Alachua, Florida.
¹⁶ Department of Radiology, Yale University, New Haven, Connecticut.

PMID: 33714667
DOI: 10.1016/j.acra.2020.12.026

Abstract

Artificial intelligence (AI) systems play an increasingly important role in all parts of the imaging chain, from image creation to image interpretation to report generation. In order to responsibly manage radiology AI systems and make informed purchase decisions about them, radiologists must understand the underlying principles of AI. Our task force was formed by the Radiology Research Alliance (RRA) of the Association of University Radiologists to identify and summarize a curated list of current educational materials available for radiologists.

Keywords: artificial intelligence; deep learning; education; machine learning; radiology.

Publication types

Review

MeSH terms

Artificial Intelligence*
Humans
Radiography
Radiologists
Radiology*