Risk stratification in neuroblastoma patients through machine learning in the multicenter PRIMAGE cohort
Our results suggested that radiomics features improve current risk stratification systems in patients with neuroblastoma.
Authors
- Adela Cañete-Nieto
- Diana Veiga-Canuto (ORCID: https://orcid.org/0000-0002-6048-2940)
- Ángel Alberich‐Bayarri (ORCID: https://orcid.org/0000-0002-5932-2392)
- Ana Jiménez-Pastor (ORCID: https://orcid.org/0000-0002-0978-9429)
- Almudena Fuster-Matanzo (ORCID: https://orcid.org/0000-0001-8667-4011)
- Sabine Taschner‐Mandl (ORCID: https://orcid.org/0000-0002-1439-5301)
- Barbara Hero (ORCID: https://orcid.org/0000-0003-4129-890X)
- Luis Martí‐Bonmatí (ORCID: https://orcid.org/0000-0002-8234-010X)
- Thorsten Simon (ORCID: https://orcid.org/0000-0002-3425-8451)
- Glen J. Weiss (ORCID: https://orcid.org/0000-0002-6067-597X)
- Jose Lozano-Montoya
- L. Cerdá Alberich (ORCID: https://orcid.org/0000-0002-5567-4278)
- Ruth Ladenstein
- Blanca Martínez-de-Las-Heras
Institutions
- University of Cologne (DE)
- Hospital Universitari i Politècnic La Fe (ES)
- St Anna Children's Hospital (AT)
- University Hospital Cologne (DE)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-02-21
- DOI
- https://doi.org/10.3389/fonc.2025.1528836
- Citations
- 3
- Primary Topic
- Neuroblastoma Research and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 4.17
Funders
- European Commission