default author photo

Pablo Hervella

affiliation not provided to SSRN

  • affiliation not provided to SSRN

SCHOLARLY PAPERS

1

DOWNLOADS

31

TOTAL CITATIONS

0

Scholarly Papers (1)

Actions:
Email selected abstracts
1.

MRI-Based Radiomics and Deep Learning for Predicting Tumor Volume and Survival in a Rat Glioblastoma Model

Number of pages: 28 Posted: 25 Mar 2026
Sara Ortega Espina, Sabela Fernández Rodicio, Bernardo Rebollo-Montes, Pelayo García-Acevedo, Ana Sampedro, Marcos Bazarra-Barreiros, Maria Teresa Abengoza-Bello, Antonio J Mosqueira, Jacobo Porto-Álvarez, Javier Martínez-Fernández, Crhistian-Mario Oblitas, José Castillo, Pablo Hervella and Ramon Iglesias-Rey
affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Universidade de Santiago de Compostela, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, affiliation not provided to SSRN, Universidade de Santiago de Compostela - Health Research Institute of Santiago de Compostela (IDIS), affiliation not provided to SSRN and Universidade de Santiago de Compostela - Health Research Institute of Santiago de Compostela (IDIS)
Downloads 31 (1,372,601)

Abstract:

Loading...

Radiomics, Deep Learning, Magnetic Resonance Imaging (MRI), Glioblastoma, Tumor prediction