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Synthesizing time-series wound prognosis factors from electronic medical records using generative adversarial networks.
Foomani, Farnaz H; Anisuzzaman, D M; Niezgoda, Jeffrey; Niezgoda, Jonathan; Guns, William; Gopalakrishnan, Sandeep; Yu, Zeyun.
Afiliação
  • Foomani FH; Department of Electrical Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, United States.
  • Anisuzzaman DM; Department of Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI, United States.
  • Niezgoda J; AZH Wound and Vascular Center, Milwaukee, WI, United States.
  • Niezgoda J; AZH Wound and Vascular Center, Milwaukee, WI, United States.
  • Guns W; AZH Wound and Vascular Center, Milwaukee, WI, United States.
  • Gopalakrishnan S; College of Nursing, University of Wisconsin-Milwaukee, Milwaukee, WI, United States. Electronic address: sandeep@uwm.edu.
  • Yu Z; Department of Electrical Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, United States; Department of Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI, United States. Electronic address: yuz@uwm.edu.
J Biomed Inform ; 125: 103972, 2022 01.
Article em En | MEDLINE | ID: mdl-34920125
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Confidencialidade / Registros Eletrônicos de Saúde Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Confidencialidade / Registros Eletrônicos de Saúde Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article