FBENet: Feature-Level Boosting Ensemble Network for Hashimoto's Thyroiditis Ultrasound Image Classification-Reference-Cited by-同舟云学术

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FBENet: Feature-Level Boosting Ensemble Network for Hashimoto's Thyroiditis Ultrasound Image Classification

Published:2024-09 Issue:9 Volume:28 Page:5360-5369
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Jiang Wenchao¹^ORCID,Luo Tianchun¹^ORCID,Liang Zhipeng¹,Chen Kang¹^ORCID,He Ji²^ORCID,Zhao Zhiming³^ORCID,Wen Jianxuan⁴^ORCID,Zhao Ling⁴^ORCID,Song Wei⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China

2. Fourth Affiliated Hospital, Guangzhou Medical University, Guangzhou, China

3. Multiscale Networked Systems Research Group, University of Amsterdam, Amsterdam, The Netherlands

4. The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China

Funder

EU H2020 CLARIFY

Guangdong Science and Technology Plan

Guangdong Natural Science Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6221020/10666866/10557590.pdf?arnumber=10557590

Reference43 articles.

1. Hashimoto's thyroiditis: An update on pathogenic mechanisms, diagnostic protocols, therapeutic strategies, and potential malignant transformation

2. Hashimotos’ thyroiditis: Epidemiology, pathogenesis, clinic and therapy

3. Reassessing Selenium for the Management of Hashimoto's Thyroiditis: The Selini Shines Bright for Autoimmune Thyroiditis Patients

4. Ultrasonography in diagnosis of Hashimoto rsquo s thyroiditis

5. ImageNet classification with deep convolutional neural networks

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