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J Am Coll Radiol. 2018 Feb;15(2):350-359. doi: 10.1016/j.jacr.2017.09.044. Epub 2017 Nov 17.

Machine Learning in Radiology: Applications Beyond Image Interpretation.

Author information

1
Department of Radiology, Thomas Jefferson University Hospital, Sidney Kimmel Jefferson Medical College, Philadelphia, Pennsylvania. Electronic address: paras.lakhani@jefferson.edu.
2
Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia.
3
Radiology Alliance, Colorado Springs, Colorado; Medical Center Radiologists, Virginia Beach, Virginia.
4
Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
5
Department of Radiology, Massachusetts General Hospital, Harvard Medical School Boston, Massachusetts.
6
I.B.M. Watson Research, Yorktown Heights, New York; Department of Radiology, University of Virginia, Charlottesville, Virginia; Medical Center Radiologists, Virginia Beach, Virginia.
7
Department of Radiology, Ohio State University Medical Center, Columbus, Ohio.
8
University of Colorado Medical Center, Denver, Colorado.
9
Department of Radiology, University of Virginia, Charlottesville, Virginia.

Abstract

Much attention has been given to machine learning and its perceived impact in radiology, particularly in light of recent success with image classification in international competitions. However, machine learning is likely to impact radiology outside of image interpretation long before a fully functional "machine radiologist" is implemented in practice. Here, we describe an overview of machine learning, its application to radiology and other domains, and many cases of use that do not involve image interpretation. We hope that better understanding of these potential applications will help radiology practices prepare for the future and realize performance improvement and efficiency gains.

KEYWORDS:

Artificial intelligence; deep learning; machine learning; radiology; workflows

PMID:
29158061
DOI:
10.1016/j.jacr.2017.09.044
[Indexed for MEDLINE]

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