A Multi-Center, Multi-Vendor Study to Evaluate the Generalizability of a Radiomics Model for Classifying Prostate cancer: High Grade vs. Low Grade.

Castillo T, Jose M; Starmans, Martijn P A; Arif, Muhammad; Niessen, Wiro J; Klein, Stefan; Bangma, Chris H; Schoots, Ivo G; Veenland, Jifke F

Castillo T, Jose M; Starmans, Martijn P A; Arif, Muhammad; Niessen, Wiro J; Klein, Stefan; Bangma, Chris H; Schoots, Ivo G; Veenland, Jifke F.

Afiliación

Castillo T JM; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Starmans MPA; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Arif M; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Niessen WJ; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Klein S; Faculty of Applied Sciences, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlands.
Bangma CH; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Schoots IG; Department of Urology, Erasmus MC, 3015 GD Rotterdam, The Netherlands.
Veenland JF; Department of Radiology and Nuclear Medicine, Erasmus MC, 3015 GD Rotterdam, The Netherlands.

Diagnostics (Basel) ; 11(2)2021 Feb 22.

Article en En | MEDLINE | ID: mdl-33671533

Palabras clave

MRI; machine learning; prostate carcinoma; radiomics

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Prognostic_studies Idioma: En Revista: Diagnostics (Basel) Año: 2021 Tipo del documento: Article País de afiliación: Países Bajos Pais de publicación: Suiza

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google