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Extracting biomedical relation from cross-sentence text using syntactic dependency graph attention network.
Zhou, Xueyang; Fu, Qiming; Chen, Jianping; Liu, Lanhui; Wang, Yunzhe; Lu, You; Wu, Hongjie.
Afiliação
  • Zhou X; Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China; Jiangsu Province Key Laboratory of Intelligent Building Energy Efficiency, Suzhou University of Science and Technology, Suzhou 215009, China.
  • Fu Q; Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China; Jiangsu Province Key Laboratory of Intelligent Building Energy Efficiency, Suzhou University of Science and Technology, Suzhou 215009, China. Electronic address: fqm_1@126.com.
  • Chen J; Jiangsu Province Key Laboratory of Intelligent Building Energy Efficiency, Suzhou University of Science and Technology, Suzhou 215009, China; Architecture and Urban Planning, Suzhou University of Science and Technology, Suzhou 215009, China; Chongqing Industrial Big Data Innovation Center Co., Ltd.,
  • Liu L; Chongqing Industrial Big Data Innovation Center Co., Ltd., Chongqing 4007071, China.
  • Wang Y; Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China; Jiangsu Province Key Laboratory of Intelligent Building Energy Efficiency, Suzhou University of Science and Technology, Suzhou 215009, China.
  • Lu Y; Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China; Jiangsu Province Key Laboratory of Intelligent Building Energy Efficiency, Suzhou University of Science and Technology, Suzhou 215009, China.
  • Wu H; Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China.
J Biomed Inform ; 144: 104445, 2023 08.
Article em En | MEDLINE | ID: mdl-37467835
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa Biomédica / Idioma Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
PubMed Links
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa Biomédica / Idioma Idioma: En Ano de publicação: 2023 Tipo de documento: Article