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PK-RNN-V E: A deep learning model approach to vancomycin therapeutic drug monitoring using electronic health record data.
Nigo, Masayuki; Tran, Hong Thoai Nga; Xie, Ziqian; Feng, Han; Mao, Bingyu; Rasmy, Laila; Miao, Hongyu; Zhi, Degui.
Afiliação
  • Nigo M; Division of Infectious Diseases, Department of Internal Medicine, The University of Texas Health Science Center at Houston, McGovern Medical School, Houston, TX, United States; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States. Electro
  • Tran HTN; Landmark Health, Huntington Beach, CA, United States.
  • Xie Z; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States.
  • Feng H; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States.
  • Mao B; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States.
  • Rasmy L; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States.
  • Miao H; School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, United States.
  • Zhi D; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, United States. Electronic address: Degui.Zhi@uth.tmc.edu.
J Biomed Inform ; 133: 104166, 2022 09.
Article em En | MEDLINE | ID: mdl-35985620
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Vancomicina / Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: J Biomed Inform Ano de publicação: 2022 Tipo de documento: Article
Texto completo
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Vancomicina / Aprendizado Profundo Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: J Biomed Inform Ano de publicação: 2022 Tipo de documento: Article