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Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning.
Pataki, Bálint Ármin; Matamoros, Sébastien; van der Putten, Boas C L; Remondini, Daniel; Giampieri, Enrico; Aytan-Aktug, Derya; Hendriksen, Rene S; Lund, Ole; Csabai, István; Schultsz, Constance.
Afiliação
  • Pataki BÁ; Department of Physics of Complex Systems, ELTE Eötvös Loránd University, Budapest, Hungary. patbaa@caesar.elte.hu.
  • Matamoros S; Department of Computational Sciences, Wigner Research Centre for Physics of the HAS, Budapest, Hungary. patbaa@caesar.elte.hu.
  • van der Putten BCL; Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
  • Remondini D; Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
  • Giampieri E; Department of Global Health, Amsterdam Institute for Global Health and Development, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
  • Aytan-Aktug D; Department of Physics and Astronomy (DIFA), University of Bologna, Bologna, Italy.
  • Hendriksen RS; Department of Experimental, Diagnostic and Specialty Medicine (DIMES), University of Bologna, Bologna, Italy.
  • Lund O; National Food Institute, Technical University of Denmark, Lyngby, Denmark.
  • Csabai I; National Food Institute, Technical University of Denmark, Lyngby, Denmark.
  • Schultsz C; Department of Bioinformatics, Technical University of Denmark, Lyngby, Denmark.
Sci Rep ; 10(1): 15026, 2020 09 14.
Article em En | MEDLINE | ID: mdl-32929164
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ciprofloxacina / Farmacorresistência Bacteriana / Aprendizado de Máquina / Genes Bacterianos / Antibacterianos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Hungria País de publicação: Reino Unido
Texto completo
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ciprofloxacina / Farmacorresistência Bacteriana / Aprendizado de Máquina / Genes Bacterianos / Antibacterianos Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Hungria País de publicação: Reino Unido