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

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...

Full description

Saved in:
Bibliographic Details
Main Authors: 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: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Oncology
Subjects:
risk stratification
neuroblastoma
overall survival
pediatric
machine learning
PRIMAGE
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1528836/full
Tags: Add Tag
No Tags, Be the first to tag this record!
Be the first to leave a comment!
You must be logged in first

Similar Items