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Application of unsupervised deep learning algorithms for identification of specific clusters of chronic cough patients from EMR data.
Shao, Wei; Luo, Xiao; Zhang, Zuoyi; Han, Zhi; Chandrasekaran, Vasu; Turzhitsky, Vladimir; Bali, Vishal; Roberts, Anna R; Metzger, Megan; Baker, Jarod; La Rosa, Carmen; Weaver, Jessica; Dexter, Paul; Huang, Kun.
Afiliación
  • Shao W; Indiana University School of Medicine, 1101 W 10th Street, Indianapolis, IN, 46202, USA.
  • Luo X; Purdue School of Engineering and Technology, IUPUI, ET 301L, 799 W. Michigan Street, Indianapolis, IN, 46202, USA. luo25@iupui.edu.
  • Zhang Z; Indiana University School of Medicine, 1101 W 10th Street, Indianapolis, IN, 46202, USA.
  • Han Z; Indiana University School of Medicine, 1101 W 10th Street, Indianapolis, IN, 46202, USA.
  • Chandrasekaran V; Regenstrief Institute, Inc., Indianapolis, IN, USA.
  • Turzhitsky V; Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ, USA.
  • Bali V; Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ, USA.
  • Roberts AR; Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ, USA.
  • Metzger M; Regenstrief Institute, Inc., Indianapolis, IN, USA.
  • Baker J; Regenstrief Institute, Inc., Indianapolis, IN, USA.
  • La Rosa C; Regenstrief Institute, Inc., Indianapolis, IN, USA.
  • Weaver J; Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ, USA.
  • Dexter P; Center for Observational and Real-World Evidence, Merck & Co., Inc., Kenilworth, NJ, USA.
  • Huang K; Indiana University School of Medicine, 1101 W 10th Street, Indianapolis, IN, 46202, USA.
BMC Bioinformatics ; 23(Suppl 3): 140, 2022 Apr 19.
Article en En | MEDLINE | ID: mdl-35439945
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Adult / Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
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PubMed Links
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Diagnostic_studies / Prognostic_studies Límite: Adult / Humans Idioma: En Revista: BMC Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos