Risk stratification in neuroblastoma patients through machine learning in the multicenter PRIMAGE cohort

IntroductionNeuroblastoma, the most prevalent solid cancer in children, presents significant biological and clinical heterogeneity. This inherent heterogeneity underscores the need for more precise prognostic markers at the time of diagnosis to enhance patient stratification, allowing for more perso...

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Autors principals:	Jose Lozano-Montoya, Ana Jimenez-Pastor, Almudena Fuster-Matanzo, Glen J. Weiss, Leonor Cerda-Alberich, Diana Veiga-Canuto, Blanca Martínez-de-Las-Heras, Adela Cañete-Nieto, Sabine Taschner-Mandl, Barbara Hero, Thorsten Simon, Ruth Ladenstein, Luis Marti-Bonmati, Angel Alberich-Bayarri
Format:	Artigo
Idioma:	Inglês
Publicat:	Frontiers Media S.A. 2025-02-01
Col·lecció:	Frontiers in Oncology
Matèries:	risk stratification neuroblastoma overall survival pediatric machine learning PRIMAGE
Accés en línia:	https://www.frontiersin.org/articles/10.3389/fonc.2025.1528836/full
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