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Deep Learning Analysis of Vibrational Spectra of Bacterial Lysate for Rapid Antimicrobial Susceptibility Testing.
Thrift, William John; Ronaghi, Sasha; Samad, Muntaha; Wei, Hong; Nguyen, Dean Gia; Cabuslay, Antony Superio; Groome, Chloe E; Santiago, Peter Joseph; Baldi, Pierre; Hochbaum, Allon I; Ragan, Regina.
Afiliación
  • Thrift WJ; Department of Materials Science and Engineering, University of California, Irvine, California 92697, United States.
  • Ronaghi S; Sage Hill School, Newport Coast, California 92657, United States.
  • Samad M; Department of Computer Science, University of California, Irvine, California 92697, United States.
  • Wei H; Department of Materials Science and Engineering, University of California, Irvine, California 92697, United States.
  • Nguyen DG; Department of Chemical and Biomolecular Engineering, University of California, Irvine, California 92697, United States.
  • Cabuslay AS; Department of Chemistry, University of California, Irvine, California 92617, United States.
  • Groome CE; Department of Materials Science and Engineering, University of California, Irvine, California 92697, United States.
  • Santiago PJ; Department of Materials Science and Engineering, University of California, Irvine, California 92697, United States.
  • Baldi P; Department of Computer Science, University of California, Irvine, California 92697, United States.
  • Hochbaum AI; Department of Materials Science and Engineering, University of California, Irvine, California 92697, United States.
  • Ragan R; Department of Chemistry, University of California, Irvine, California 92617, United States.
ACS Nano ; 14(11): 15336-15348, 2020 11 24.
Article en En | MEDLINE | ID: mdl-33095005
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Nano Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Aprendizaje Profundo Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Nano Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos