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Editorial

. 2022 Jan;302(1):198-199.

doi: 10.1148/radiol.2021210731. Epub 2021 Oct 12.

Artificial Intelligence for Interstitial Lung Disease: Proudly Supporting Radiologists Since 2021

Mark O Wielpütz¹

Affiliations

Affiliation

¹ From the Translational Lung Research Center (TLRC), German Lung Research Center, University of Heidelberg, Heidelberg, Germany; Department of Diagnostic and Interventional Radiology, University of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany; and Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany.

PMID: 34636638
DOI: 10.1148/radiol.2021210731

Editorial

Artificial Intelligence for Interstitial Lung Disease: Proudly Supporting Radiologists Since 2021

Mark O Wielpütz. Radiology. 2022 Jan.

. 2022 Jan;302(1):198-199.

doi: 10.1148/radiol.2021210731. Epub 2021 Oct 12.

Author

Mark O Wielpütz¹

Affiliation

¹ From the Translational Lung Research Center (TLRC), German Lung Research Center, University of Heidelberg, Heidelberg, Germany; Department of Diagnostic and Interventional Radiology, University of Heidelberg, Im Neuenheimer Feld 420, 69120 Heidelberg, Germany; and Department of Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University of Heidelberg, Heidelberg, Germany.

PMID: 34636638
DOI: 10.1148/radiol.2021210731

No abstract available

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Comment on

Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT.
Choe J, Hwang HJ, Seo JB, Lee SM, Yun J, Kim MJ, Jeong J, Lee Y, Jin K, Park R, Kim J, Jeon H, Kim N, Yi J, Yu D, Kim B. Choe J, et al. Radiology. 2022 Jan;302(1):187-197. doi: 10.1148/radiol.2021204164. Epub 2021 Oct 12. Radiology. 2022. PMID: 34636634

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