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Machine Learning Integrated Workflow for Predicting Schwann Cell Viability on Conductive MXene Biointerfaces.
Chung, Tsai-Chun; Hsu, Ya-Hsin; Chen, Tianle; Li, Yang; Yang, Haochen; Yu, Jin-Xiu; Lee, I-Chi; Lai, Ping-Shan; Li, Yi-Chen Ethan; Chen, Po-Yen.
Afiliação
  • Chung TC; Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, Maryland 20742, United States.
  • Hsu YH; Department of Chemistry, National Chung Hsing University, Taichung 402202, Taiwan.
  • Chen T; Department of Chemical Engineering, Feng Chia University, Taichung 407102, Taiwan.
  • Li Y; Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, Maryland 20742, United States.
  • Yang H; Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, Maryland 20742, United States.
  • Yu JX; Department of Chemical and Biomolecular Engineering, University of Maryland, College Park, Maryland 20742, United States.
  • Lee IC; Department of Chemical Engineering, Feng Chia University, Taichung 407102, Taiwan.
  • Lai PS; Department of Biomedical Engineering and Environmental Sciences, National Tsing Hua University, Hsinchu 300044, Taiwan.
  • Li YE; Department of Chemistry, National Chung Hsing University, Taichung 402202, Taiwan.
  • Chen PY; Department of Chemical Engineering, Feng Chia University, Taichung 407102, Taiwan.
ACS Appl Mater Interfaces ; 15(39): 46460-46469, 2023 Oct 04.
Article em En | MEDLINE | ID: mdl-37733022
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article
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 Ano de publicação: 2023 Tipo de documento: Article