Convolutional Neural Network to Stratify the Malignancy Risk of Thyroid Nodules: Diagnostic Performance Compared with the American College of Radiology Thyroid Imaging Reporting and Data System Implemented by Experienced Radiologists

G.R. Kim; E. Lee; H.R. Kim; J.H. Yoon; V.Y. Park; J.Y. Kwak

doi:10.3174/ajnr.A7149

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Convolutional Neural Network to Stratify the Malignancy Risk of Thyroid Nodules: Diagnostic Performance Compared with the American College of Radiology Thyroid Imaging Reporting and Data System Implemented by Experienced Radiologists

G.R. Kim, E. Lee, H.R. Kim, J.H. Yoon, V.Y. Park and J.Y. Kwak

American Journal of Neuroradiology August 2021, 42 (8) 1513-1519; DOI: https://doi.org/10.3174/ajnr.A7149

G.R. Kim

aFrom the Department of Radiology (G.R.K., J.H.Y., V.Y.P., J.Y.K.), Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea

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E. Lee

bDepartment of Computational Science and Engineering (E.L.), Yonsei University, Seoul, Korea

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H.R. Kim

cBiostatistics Collaboration Unit (H.R.K.), Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea

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J.H. Yoon

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V.Y. Park

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J.Y. Kwak

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vol. 42 no. 8 1513-1519

DOI

https://doi.org/10.3174/ajnr.A7149

PubMed

33985947

Published By

American Journal of Neuroradiology

Print ISSN

0195-6108

Online ISSN

1936-959X

History

Received August 5, 2020
Accepted after revision March 6, 2021
Published online August 11, 2021.

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Latest version (May 13, 2021 - 06:52).
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Author Information

G.R. Kima,
E. Leeb,
H.R. Kimc,
J.H. Yoona,
V.Y. Parka and
J.Y. Kwaka

^aFrom the Department of Radiology (G.R.K., J.H.Y., V.Y.P., J.Y.K.), Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, Korea
^bDepartment of Computational Science and Engineering (E.L.), Yonsei University, Seoul, Korea
^cBiostatistics Collaboration Unit (H.R.K.), Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea

Please address correspondence to Jin Young Kwak, MD, PhD, Department of Radiology, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea, 120-752; e-mail: docjin{at}yuhs.ac

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Funding

National Research Foundation of Korea
2019R1A2C1002375
CMB-Yuhan research grant of Yonsei University College of Medicine
6-2017-0170

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Cite this article

G.R. Kim, E. Lee, H.R. Kim, J.H. Yoon, V.Y. Park, J.Y. Kwak

Convolutional Neural Network to Stratify the Malignancy Risk of Thyroid Nodules: Diagnostic Performance Compared with the American College of Radiology Thyroid Imaging Reporting and Data System Implemented by Experienced Radiologists

American Journal of Neuroradiology Aug 2021, 42 (8) 1513-1519; DOI: 10.3174/ajnr.A7149

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G.R. Kim, E. Lee, H.R. Kim, J.H. Yoon, V.Y. Park, J.Y. Kwak

American Journal of Neuroradiology Aug 2021, 42 (8) 1513-1519; DOI: 10.3174/ajnr.A7149

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Convolutional Neural Network to Stratify the Malignancy Risk of Thyroid Nodules: Diagnostic Performance Compared with the American College of Radiology Thyroid Imaging Reporting and Data System Implemented by Experienced Radiologists

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National Research Foundation of Korea

CMB-Yuhan research grant of Yonsei University College of Medicine

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