Using Artificial Intelligence to Revise ACR TI-RADS Risk Stratification of Thyroid Nodules: Diagnostic Accuracy and Utility-Reference-Cited by-同舟云学术

Using Artificial Intelligence to Revise ACR TI-RADS Risk Stratification of Thyroid Nodules: Diagnostic Accuracy and Utility

Published:2019-07 Issue:1 Volume:292 Page:112-119
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Wildman-Tobriner Benjamin¹^ORCID,Buda Mateusz¹^ORCID,Hoang Jenny K.¹^ORCID,Middleton William D.¹,Thayer David¹^ORCID,Short Ryan G.¹^ORCID,Tessler Franklin N.¹^ORCID,Mazurowski Maciej A.¹^ORCID

Affiliation:

1. From the Department of Radiology, Duke University Hospital, 2301 Erwin Rd, Durham, NC 27701 (B.W.T., M.B., J.K.H., R.G.S., M.A.M.); Mallinckrodt Institute of Radiology, Washington University School of Medicine, St Louis, Mo (W.D.M., D.T.); and Department of Radiology, University of Alabama at Birmingham, Birmingham, Ala (F.N.T.).

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology, Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.2019182128

Reference20 articles.

1. Managing Incidental Thyroid Nodules Detected on Imaging: White Paper of the ACR Incidental Thyroid Findings Committee

2. Risk of Thyroid Cancer Based on Thyroid Ultrasound Imaging Characteristics

3. Applying the Society of Radiologists in Ultrasound Recommendations for Fine-Needle Aspiration of Thyroid Nodules: Effect on Workup and Malignancy Detection

4. Worldwide Thyroid-Cancer Epidemic? The Increasing Impact of Overdiagnosis

5. ACR Thyroid Imaging, Reporting and Data System (TI-RADS): White Paper of the ACR TI-RADS Committee

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