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Development of benchmark datasets for text mining and sentiment analysis to accelerate regulatory literature review.
Wu, Leihong; Chen, Si; Guo, Lei; Shpyleva, Svitlana; Harris, Kelly; Fahmi, Tariq; Flanigan, Timothy; Tong, Weida; Xu, Joshua; Ren, Zhen.
Afiliação
  • Wu L; Division of Bioinformatics and Biostatics, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA. Electronic address: leihong.wu@fda.hhs.gov.
  • Chen S; Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA.
  • Guo L; Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA.
  • Shpyleva S; Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA.
  • Harris K; Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA.
  • Fahmi T; Office of Scientific Coordination, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA.
  • Flanigan T; Division of Neurotoxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA.
  • Tong W; Division of Bioinformatics and Biostatics, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA.
  • Xu J; Division of Bioinformatics and Biostatics, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA.
  • Ren Z; Division of Biochemical Toxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR, 72079, USA. Electronic address: zhen.ren@fda.hhs.gov.
Regul Toxicol Pharmacol ; 137: 105287, 2023 Jan.
Article em En | MEDLINE | ID: mdl-36372266
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Aprendizado de Máquina Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Aprendizado de Máquina Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article