Noninterpretive Uses of Artificial Intelligence in Radiology

Michael L Richardson; Elisabeth R Garwood; Yueh Lee; Matthew D Li; Hao S Lo; Arun Nagaraju; Xuan V Nguyen; Linda Probyn; Prabhakar Rajiah; Jessica Sin; Ashish P Wasnik; Kali Xu

doi:10.1016/j.acra.2020.01.012

Noninterpretive Uses of Artificial Intelligence in Radiology

Acad Radiol. 2021 Sep;28(9):1225-1235. doi: 10.1016/j.acra.2020.01.012. Epub 2020 Feb 12.

Authors

Michael L Richardson¹, Elisabeth R Garwood², Yueh Lee³, Matthew D Li⁴, Hao S Lo⁵, Arun Nagaraju⁶, Xuan V Nguyen⁷, Linda Probyn⁸, Prabhakar Rajiah⁹, Jessica Sin¹⁰, Ashish P Wasnik¹¹, Kali Xu¹²

Affiliations

¹ Department of Radiology, University of Washington, Seattle, Washington. Electronic address: mrich@uw.edu.
² Department of Radiology, University of Massachusetts, Worcester, Massachusetts.
³ Department of Radiology, University of North Carolina, Chapel Hill, North Carolina.
⁴ Department of Radiology, Harvard Medical School/Massachusetts General Hospital, Boston, Massachusets.
⁵ Department of Radiology, University of Washington, Seattle, Washington.
⁶ Department of Radiology, University of Chicago, Chicago, Illinois.
⁷ Department of Radiology, The Ohio State University Wexner Medical Center, Columbus, Ohio.
⁸ Department of Radiology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario.
⁹ Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas.
¹⁰ Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire.
¹¹ Department of Radiology, University of Michigan, Ann Arbor, Michigan.
¹² Department of Medicine, Santa Clara Valley Medical Center, Santa Clara, California.

PMID: 32059956
DOI: 10.1016/j.acra.2020.01.012

Abstract

We deem a computer to exhibit artificial intelligence (AI) when it performs a task that would normally require intelligent action by a human. Much of the recent excitement about AI in the medical literature has revolved around the ability of AI models to recognize anatomy and detect pathology on medical images, sometimes at the level of expert physicians. However, AI can also be used to solve a wide range of noninterpretive problems that are relevant to radiologists and their patients. This review summarizes some of the newer noninterpretive uses of AI in radiology.

Keywords: Artificial intelligence; Deep learning; Radiology applications; Radiology education.

Publication types

Review

MeSH terms

Artificial Intelligence*
Humans
Radiography
Radiologists
Radiology*