An Artificial Intelligence Model Based on ACR TI-RADS Characteristics for US Diagnosis of Thyroid Nodules-Reference-Cited by-同舟云学术

An Artificial Intelligence Model Based on ACR TI-RADS Characteristics for US Diagnosis of Thyroid Nodules

Published:2022-06 Issue:3 Volume:303 Page:613-619
ISSN:0033-8419
Container-title:Radiology
language:en
Short-container-title:Radiology

Author:

Chen Yufan^ORCID,Gao Zixiong^ORCID,He Yanni^ORCID,Mai Wuping^ORCID,Li Jinhua^ORCID,Zhou Meijun^ORCID,Li Sushu,Yi Wenhong^ORCID,Wu Shuyu^ORCID,Bai Tong^ORCID,Zhang Ning^ORCID,Zeng Weibo^ORCID,Lu Yao^ORCID,Liu Hongmei^ORCID

Funder

NSFC

Science and Technology Program of Guangzhou

Department of Science and Technology of Jilin Province

Shanghi Key Laboratory of Molecular Imaging

Guangdong Province Key Laboratory of Computational Science

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology, Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/radiol.211455

Reference22 articles.

1. The Diagnosis and Management of Thyroid Nodules

2. Global trends in thyroid cancer incidence and the impact of overdiagnosis

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

4. Diagnostic performance of US-based FNAB criteria of the 2020 Chinese guideline for malignant thyroid nodules: comparison with the 2017 American College of Radiology guideline, the 2015 American Thyroid Association guideline, and the 2016 Korean Thyroid Association guideline

5. Diagnostic Performance of Practice Guidelines for Thyroid Nodules: Thyroid Nodule Size versus Biopsy Rates

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