Deep learning prediction of overall survival in glioblastoma patients using pre-chemoradiotherapy MRI and clinical data
- DOI
- 10.3389/fradi.2026.1963539
- Published
- 10
- Container
- Frontiers in Radiology
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3389/fradi.2026.1963539,
title = {Deep learning prediction of overall survival in glioblastoma patients using pre-chemoradiotherapy MRI and clinical data},
author = {Noémie N. Moreau and Noémie N. Moreau and Alexis Desmonts and Alexis Desmonts and Alexis Desmonts and Cyril Jaudet and Thomas Leleu and Alexandre G. Leclercq and Alexandre G. Leclercq and Alexandre G. Leclercq and Carole Brunaud and Dinu Stefan and Samuel Valable and Alexis Lechervy and Aurélien Corroyer-Dulmont and Aurélien Corroyer-Dulmont and Aurélien Corroyer-Dulmont},
year = {2026},
journal = {Frontiers in Radiology},
doi = {10.3389/fradi.2026.1963539},
url = {https://doi.org/10.3389/fradi.2026.1963539}
}RIS
TY - JOUR TI - Deep learning prediction of overall survival in glioblastoma patients using pre-chemoradiotherapy MRI and clinical data AU - Noémie N. Moreau AU - Noémie N. Moreau AU - Alexis Desmonts AU - Alexis Desmonts AU - Alexis Desmonts AU - Cyril Jaudet AU - Thomas Leleu AU - Alexandre G. Leclercq AU - Alexandre G. Leclercq AU - Alexandre G. Leclercq AU - Carole Brunaud AU - Dinu Stefan AU - Samuel Valable AU - Alexis Lechervy AU - Aurélien Corroyer-Dulmont AU - Aurélien Corroyer-Dulmont AU - Aurélien Corroyer-Dulmont PY - 2026 JO - Frontiers in Radiology DO - 10.3389/fradi.2026.1963539 UR - https://doi.org/10.3389/fradi.2026.1963539 ER -
APA
Moreau, N. N., Moreau, N. N., Desmonts, A., Desmonts, A., Desmonts, A., Jaudet, C., Leleu, T., Leclercq, A. G., Leclercq, A. G., Leclercq, A. G., Brunaud, C., Stefan, D., Valable, S., Lechervy, A., Corroyer-Dulmont, A., Corroyer-Dulmont, A., & Corroyer-Dulmont, A. (2026). Deep learning prediction of overall survival in glioblastoma patients using pre-chemoradiotherapy MRI and clinical data. Frontiers in Radiology. https://doi.org/10.3389/fradi.2026.1963539