Author:
Islam Mobarakol,Vibashan V. S.,Jose V. Jeya Maria,Wijethilake Navodini,Utkarsh Uppal,Ren Hongliang
Publisher
Springer International Publishing
Reference21 articles.
1. Bakas, S., et al.: Segmentation labels and radiomic features for the pre-operative scans of the TCGA-GBM collection. Cancer Imaging Arch. 286 (2017)
2. Bakas, S., et al.: Advancing the Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features. Sci. Data 4, 170117 (2017)
3. Bakas, S., et al.: Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the brats challenge. arXiv preprint
arXiv:1811.02629
(2018)
4. Castells, X., et al.: Automated brain tumor biopsy prediction using single-labeling cDNA microarrays-based gene expression profiling. Diagn. Mol. Pathol. 18(4), 206–218 (2009)
5. Chen, T., Guestrin, C.: XGBoost: a scalable tree boosting system. In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 785–794. ACM (2016)
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