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Evaluation of radiomics and machine learning in identification of aggressive tumor features in renal cell carcinoma (RCC).
Gurbani, Sidharth; Morgan, Dane; Jog, Varun; Dreyfuss, Leo; Shen, Mingren; Das, Arighno; Abel, E Jason; Lubner, Meghan G.
Afiliación
  • Gurbani S; Department of Electrical and Computer Engineering, University of Wisconsin College of Engineering, Madison, WI, USA.
  • Morgan D; Department of Material Science and Engineering, University of Wisconsin College of Engineering, Madison, WI, USA.
  • Jog V; Department of Electrical and Computer Engineering, University of Wisconsin College of Engineering, Madison, WI, USA.
  • Dreyfuss L; Department of Urology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
  • Shen M; Department of Radiology, School of Medicine and Public Health, University of Wisconsin, E3/311 Clinical Sciences Center, 600 Highland Ave, Madison, WI, 53792, USA.
  • Das A; Department of Material Science and Engineering, University of Wisconsin College of Engineering, Madison, WI, USA.
  • Abel EJ; Department of Urology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
  • Lubner MG; Department of Urology, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA.
Abdom Radiol (NY) ; 46(9): 4278-4288, 2021 09.
Article en En | MEDLINE | ID: mdl-33855609
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Carcinoma de Células Renales / Neoplasias Renales Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans / Middle aged Idioma: En Revista: Abdom Radiol (NY) Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Carcinoma de Células Renales / Neoplasias Renales Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans / Middle aged Idioma: En Revista: Abdom Radiol (NY) Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos