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Contrastive learning improves critical event prediction in COVID-19 patients.
Wanyan, Tingyi; Honarvar, Hossein; Jaladanki, Suraj K; Zang, Chengxi; Naik, Nidhi; Somani, Sulaiman; De Freitas, Jessica K; Paranjpe, Ishan; Vaid, Akhil; Zhang, Jing; Miotto, Riccardo; Wang, Zhangyang; Nadkarni, Girish N; Zitnik, Marinka; Azad, Ariful; Wang, Fei; Ding, Ying; Glicksberg, Benjamin S.
Afiliação
  • Wanyan T; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Honarvar H; School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA.
  • Jaladanki SK; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Zang C; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Naik N; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
  • Somani S; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • De Freitas JK; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Paranjpe I; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Vaid A; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Zhang J; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Miotto R; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Wang Z; Renmin University of China, Beijing, China.
  • Nadkarni GN; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Zitnik M; Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, USA.
  • Azad A; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Wang F; Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Ding Y; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Glicksberg BS; Department of Biomedical Informatics, Harvard University, USA.
Patterns (N Y) ; 2(12): 100389, 2021 Dec 10.
Article em En | MEDLINE | ID: mdl-34723227
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Patterns (N Y) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Patterns (N Y) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos