TY - JOUR
T1 - Challenges related to artificial intelligence research in medical imaging and the importance of image analysis competitions
AU - Prevedello, Luciano M.
AU - Halabi, Safwan S.
AU - Shih, George
AU - Wu, Carol C.
AU - Kohli, Marc D.
AU - Chokshi, Falgun H.
AU - Erickson, Bradley J.
AU - Kalpathy-Cramer, Jayashree
AU - Andriole, Katherine P.
AU - Flanders, Adam E.
N1 - Publisher Copyright:
© RSNA, 2019.
PY - 2019/1
Y1 - 2019/1
N2 - In recent years, there has been enormous interest in applying artificial intelligence (AI) to radiology. Although some of this interest may have been driven by exaggerated expectations that the technology can outperform radiologists in some tasks, there is a growing body of evidence that illustrates its limitations in medical imaging. The true potential of the technique probably lies somewhere in the middle, and AI will ultimately play a key role in medical imaging in the future. The limitless power of computers makes AI an ideal candidate to provide the standardization, consistency, and dependability needed to support radiologists in their mission to provide excellent patient care. However, important roadblocks currently limit the expansion of this field in medical imaging. This article reviews some of the challenges and potential solutions to advance the field forward, with focus on the experience gained by hosting image-based competitions.
AB - In recent years, there has been enormous interest in applying artificial intelligence (AI) to radiology. Although some of this interest may have been driven by exaggerated expectations that the technology can outperform radiologists in some tasks, there is a growing body of evidence that illustrates its limitations in medical imaging. The true potential of the technique probably lies somewhere in the middle, and AI will ultimately play a key role in medical imaging in the future. The limitless power of computers makes AI an ideal candidate to provide the standardization, consistency, and dependability needed to support radiologists in their mission to provide excellent patient care. However, important roadblocks currently limit the expansion of this field in medical imaging. This article reviews some of the challenges and potential solutions to advance the field forward, with focus on the experience gained by hosting image-based competitions.
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U2 - 10.1148/ryai.2019180031
DO - 10.1148/ryai.2019180031
M3 - Article
C2 - 33937783
AN - SCOPUS:85071674400
SN - 2638-6100
VL - 1
JO - Radiology: Artificial Intelligence
JF - Radiology: Artificial Intelligence
IS - 1
M1 - e180031
ER -