ASO Visual Abstract: Solid Attenuation Components Attention Deep Learning Model to Predict Micropapillary and Solid Patterns in Lung Adenocarcinomas on Computed Tomography

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Published inAnnals of surgical oncology Vol. 29; no. 12; pp. 7483 - 7484
Main Authors Chen, Li-Wei, Yang, Shun-Mao, Chuang, Ching-Chia, Wang, Hao-Jen, Chen, Yi-Chang, Lin, Mong-Wei, Hsieh, Min-Shu, Antonoff, Mara B., Chang, Yeun-Chung, Wu, Carol C., Pan, Tinsu, Chen, Chung-Ming
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.11.2022
Springer Nature B.V
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Author Antonoff, Mara B.
Chen, Chung-Ming
Hsieh, Min-Shu
Chuang, Ching-Chia
Lin, Mong-Wei
Yang, Shun-Mao
Chen, Yi-Chang
Pan, Tinsu
Chen, Li-Wei
Wang, Hao-Jen
Chang, Yeun-Chung
Wu, Carol C.
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– sequence: 2
  givenname: Shun-Mao
  surname: Yang
  fullname: Yang, Shun-Mao
  organization: Department of Biomedical Engineering, College of Medicine and College of Engineering, National Taiwan University, Department of Surgery, National Taiwan University Hospital Biomedical Park Hospital
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  givenname: Ching-Chia
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  surname: Antonoff
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  organization: Department of Thoracic and Cardiovascular Surgery, The University of Texas MD Anderson Cancer Center
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  surname: Chang
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SubjectTerms ASO Visual Abstract
Computed tomography
Deep learning
Lung cancer
Medicine
Medicine & Public Health
Oncology
Surgery
Surgical Oncology
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Title ASO Visual Abstract: Solid Attenuation Components Attention Deep Learning Model to Predict Micropapillary and Solid Patterns in Lung Adenocarcinomas on Computed Tomography
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