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A Radiomic-based Machine Learning Algorithm to Reliably Differentiate Benign Renal Masses from Renal Cell Carcinoma.
Nassiri, Nima; Maas, Marissa; Cacciamani, Giovanni; Varghese, Bino; Hwang, Darryl; Lei, Xiaomeng; Aron, Monish; Desai, Mihir; Oberai, Assad A; Cen, Steven Y; Gill, Inderbir S; Duddalwar, Vinay A.
Afiliación
  • Nassiri N; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Artificial Intelligence Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA, USA. Electr
  • Maas M; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Artificial Intelligence Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA, USA.
  • Cacciamani G; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Artificial Intelligence Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA, USA; Depart
  • Varghese B; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Hwang D; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Lei X; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Aron M; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Desai M; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Oberai AA; Artificial Intelligence Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA, USA; Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.
  • Cen SY; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Gill IS; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Artificial Intelligence Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA, USA.
  • Duddalwar VA; USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Artificial Intelligence Center at USC Urology, USC Institute of Urology, University of Southern California, Los Angeles, CA, USA; Depart
Eur Urol Focus ; 8(4): 988-994, 2022 07.
Article en En | MEDLINE | ID: mdl-34538748
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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: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Eur Urol Focus Año: 2022 Tipo del documento: Article
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: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Eur Urol Focus Año: 2022 Tipo del documento: Article