Joeky Senders
105 Glioblastoma survival calculator 17. Hilario A, Sepulveda JM, Perez-Nuñez A, et al. A Prognostic Model Based on Preoperative MRI Predicts Overall Survival in Patients with Diffuse Gliomas. American Journal of Neuroradiology. 2014;35(6):1096- 1102. doi:10.3174/ajnr.A3837 18. Cui Y, Ren S, Tha KK, Wu J, Shirato H, Li R. Volume of high-risk intratumoral subregions at multi-parametric MR imaging predicts overall survival and complements molecular analysis of glioblastoma. Eur Radiol. 2017;27(9):3583-3592. doi:10.1007/s00330-017-4751-x 19. Mazurowski MA, Desjardins A, Malof JM. Imaging descriptors improve the predictive power of survival models for glioblastoma patients. Neuro Oncol. 2013;15(10):1389-1394. doi:10.1093/neuonc/nos335 20. Cui Y, Tha KK, Terasaka S, et al. Prognostic Imaging Biomarkers in Glioblastoma: Development and Independent Validation on the Basis of Multiregion and Quantitative Analysis of MR Images. Radiology. 2015;278(2):546-553. doi:10.1148/radiol.2015150358 21. Kickingereder P, Burth S, Wick A, et al. Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models. Radiology. 2016;280(3):880-889. doi:10.1148/radiol.2016160845 22. Lao J, Chen Y, Li Z-C, et al. A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme. Scientific Reports. 2017;7(1):10353. doi:10.1038/s41598-017-10649-8 23. Li Q, Bai H, Chen Y, et al. A Fully-Automatic Multiparametric Radiomics Model: Towards Reproducible and Prognostic Imaging Signature for Prediction of Overall Survival in Glioblastoma Multiforme. Scientific Reports. 2017;7(1):14331. doi:10.1038/s41598-017-14753-7 24. Mauer MEL, Taphoorn MJB, Bottomley A, et al. Prognostic Value of Health-Related Quality-of-Life Data in Predicting Survival in Patients With Anaplastic Oligodendrogliomas, From a Phase III EORTC Brain Cancer Group Study. JCO. 2007;25(36):5731-5737. doi:10.1200/JCO.2007.11.1476 25. Gómez-Rueda H, Martínez-Ledesma E, Martínez-Torteya A, Palacios-Corona R, Trevino V. Integration and comparison of different genomic data for outcome prediction in cancer. BioData Mining. 2015;8(1):32. doi:10.1186/s13040-015-0065-1 26. Stupp R, Mason WP, van den Bent MJ, et al. Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma. New England Journal of Medicine. 2005;352(10):987-996. doi:10.1056/NEJMoa043330 27. Chiou SH, Kang S, Yan J. Fitting Accelerated Failure Time Models in Routine Survival Analysis with R Package aftgee. Journal of Statistical Software. 2014;61(11). doi:10.18637/jss.v061.i11 28. Pan SJ, Yang Q. A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering. 2010;22(10):1345-1359. doi:10.1109/TKDE.2009.191 29. Senders JT, Staples PC, Karhade AV, et al. Machine Learning and Neurosurgical Outcome Prediction: A Systematic Review. World Neurosurgery. 2018;109:476-486.e1. doi:10.1016/j.wneu.2017.09.149
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