An ensemble deep learning architecture for multilabel classification on TI-RADS

Duan, Xueli, Duan, Shaobo, Jiang, Pei, Li, Runzhi, Zhang, Ye, Ma, Jingzhe, Zhao, Hongling and Dai, Honghua 2021, An ensemble deep learning architecture for multilabel classification on TI-RADS, in BIBM 2020 : Preceedings of IEEE International Conference on Bioinformatics and Biomedicine, Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 576-582, doi: 10.1109/BIBM49941.2020.9313134.

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Title An ensemble deep learning architecture for multilabel classification on TI-RADS
Author(s) Duan, Xueli
Duan, Shaobo
Jiang, Pei
Li, Runzhi
Zhang, Ye
Ma, Jingzhe
Zhao, Hongling
Dai, HonghuaORCID iD for Dai, Honghua orcid.org/0000-0001-9899-7029
Conference name BIBM 2020 IEEE Bioinformatics and Biomedicine. International Conference (Virtual Event via Seoul, South Korea))
Conference location Virtual Event via Seoul, South Korea
Conference dates 16 - 19 Dec. 2020
Title of proceedings BIBM 2020 : Preceedings of IEEE International Conference on Bioinformatics and Biomedicine
Editor(s) Park, Taesung
Cho, Young-Rae
Hu, Xiaohua
Yoo, Illhoi
Woo, Hyun Goo
Wang, Jianxin
Facelli, Julio
Nam, Seungyoon
Kang, Mingon
Publication date 2021
Start page 576
End page 582
Total pages 7
Publisher Institute of Electrical and Electronics Engineers
Place of publication Piscataway, N.J.
Keyword(s) thyroid nodule
pathological features
TI-RADS
multi-label classification
no CORE2020
ISBN 9781728162157
Language eng
DOI 10.1109/BIBM49941.2020.9313134
Indigenous content off
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2020, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30148521

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