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Improved Prediction of Carbonless NMR Spectra by the Machine Learning of Theoretical and Fragment Descriptors for Environmental Mixture Analysis.
Ito, Kengo; Xu, Xiangru; Kikuchi, Jun.
Affiliation
  • Ito K; RIKEN Center for Sustainable Resource Science, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.
  • Xu X; Graduate School of Medical Life Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.
  • Kikuchi J; Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland.
Anal Chem ; 93(18): 6901-6906, 2021 05 11.
Article in En | MEDLINE | ID: mdl-33929838
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Magnetic Resonance Imaging / Complex Mixtures Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Anal Chem Year: 2021 Type: Article Affiliation country: Japan
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Magnetic Resonance Imaging / Complex Mixtures Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Anal Chem Year: 2021 Type: Article Affiliation country: Japan