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Value of machine learning in predicting TAVI outcomes.
Lopes, R R; van Mourik, M S; Schaft, E V; Ramos, L A; Baan, J; Vendrik, J; de Mol, B A J M; Vis, M M; Marquering, H A.
Afiliação
  • Lopes RR; Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
  • van Mourik MS; Heart Centre, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
  • Schaft EV; Technical Medicine, University of Twente, Enschede, The Netherlands.
  • Ramos LA; Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
  • Baan J; Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam UMC, Amsterdam, The Netherlands.
  • Vendrik J; Heart Centre, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
  • de Mol BAJM; Heart Centre, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
  • Vis MM; Heart Centre, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
  • Marquering HA; Heart Centre, Amsterdam UMC, University of Amsterdam, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
Neth Heart J ; 27(9): 443-450, 2019 Sep.
Article em En | MEDLINE | ID: mdl-31111457
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2019 Tipo de documento: Article