Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages
Author:
Funder
U.S. Department of Health & Human Services | NIH | NIH Clinical Center
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://www.nature.com/articles/s41598-018-37387-9.pdf
Reference64 articles.
1. Curran, W. J. Jr. et al. Recursive partitioning analysis of prognostic factors in three radiation therapy oncology group malignant glioma trials. JNCI: Journal of the National Cancer Institute 85, 704–710 (1993).
2. Gittleman, H. et al. An independently validated nomogram for individualized estimation of survival among patients with newly diagnosed glioblastoma: Nrg oncology rtog 0525 and 0825. Neuro-oncology 19, 669–677 (2017).
3. Lacroix, M. et al. A multivariate analysis of 416 patients with glioblastoma multiforme: prognosis, extent of resection, and survival. Journal of neurosurgery 95, 190–198 (2001).
4. DeAngelis, L. M. Brain tumors. New England Journal of Medicine 344, 114–123 (2001).
5. Guillamo, J.-S. et al. Brainstem gliomas in adults: prognostic factors and classification. Brain 124, 2528–2539 (2001).
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