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

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

^*Corresponding author for this work

Radiology

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

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.

Original language	English (US)
Pages (from-to)	1238-1252
Number of pages	15
Journal	Academic radiology
Volume	28
Issue number	9
DOIs	https://doi.org/10.1016/j.acra.2020.12.026
State	Published - Sep 2021

Keywords

artificial intelligence
deep learning
education
machine learning
radiology

ASJC Scopus subject areas

Radiology Nuclear Medicine and imaging

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10.1016/j.acra.2020.12.026

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Richardson, M. L., Adams, S. J., Agarwal, A., Auffermann, W. F., Bhattacharya, A. K., Consul, N., Fotos, J. S., Kelahan, L. C., Lin, C., Lo, H. S., Nguyen, X. V., Salkowski, L. R., Sin, J. M., Thomas, R. C., Wassef, S., & Ikuta, I. (2021). Review of Artificial Intelligence Training Tools and Courses for Radiologists. Academic radiology, 28(9), 1238-1252. https://doi.org/10.1016/j.acra.2020.12.026

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title = "Review of Artificial Intelligence Training Tools and Courses for Radiologists",

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",

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

note = "Publisher Copyright: {\textcopyright} 2021",

year = "2021",

month = sep,

doi = "10.1016/j.acra.2020.12.026",

language = "English (US)",

volume = "28",

pages = "1238--1252",

journal = "Academic radiology",

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Richardson, ML, Adams, SJ, Agarwal, A, Auffermann, WF, Bhattacharya, AK, Consul, N, Fotos, JS, Kelahan, LC, Lin, C, Lo, HS, Nguyen, XV, Salkowski, LR, Sin, JM, Thomas, RC, Wassef, S & Ikuta, I 2021, 'Review of Artificial Intelligence Training Tools and Courses for Radiologists', Academic radiology, vol. 28, no. 9, pp. 1238-1252. https://doi.org/10.1016/j.acra.2020.12.026

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AU - Richardson, Michael L.

AU - Adams, Scott J.

AU - Agarwal, Atul

AU - Auffermann, William F.

AU - Bhattacharya, Anup K.

AU - Consul, Nikita

AU - Fotos, Joseph S.

AU - Kelahan, Linda C.

AU - Lin, Christine

AU - Lo, Hao S.

AU - Nguyen, Xuan V.

AU - Salkowski, Lonie R.

AU - Sin, Jessica M.

AU - Thomas, Robert C.

AU - Wassef, Shafik

AU - Ikuta, Ichiro

PY - 2021/9

Y1 - 2021/9

N2 - 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.

AB - 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.

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KW - deep learning

KW - education

KW - machine learning

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Review of Artificial Intelligence Training Tools and Courses for Radiologists

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Keywords

ASJC Scopus subject areas

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