| Comprehensive, integrative genomic analysis of diffuse lower-grade gliomas Cancer Genome Atlas Research Network New England Journal of Medicine 372 (26), 2481-2498, 2015 | 3046 | 2015 |
| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2062 | 2018 |
| Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data MJ Sheller, B Edwards, GA Reina, J Martin, S Pati, A Kotrotsou, ... Scientific reports 10 (1), 12598, 2020 | 1248 | 2020 |
| The rsna-asnr-miccai brats 2021 benchmark on brain tumor segmentation and radiogenomic classification U Baid, S Ghodasara, S Mohan, M Bilello, E Calabrese, E Colak, ... arXiv preprint arXiv:2107.02314, 2021 | 739 | 2021 |
| MR imaging predictors of molecular profile and survival: multi-institutional study of the TCGA glioblastoma data set DA Gutman, LAD Cooper, SN Hwang, CA Holder, JJ Gao, TD Aurora, ... Radiology 267 (2), 560-569, 2013 | 467 | 2013 |
| Glioblastoma-infiltrated innate immune cells resemble M0 macrophage phenotype K Gabrusiewicz, B Rodriguez, J Wei, Y Hashimoto, LM Healy, SN Maiti, ... JCI insight 1 (2), 2016 | 450 | 2016 |
| Radiogenomic mapping of edema/cellular invasion MRI-phenotypes in glioblastoma multiforme PO Zinn, B Majadan, P Sathyan, SK Singh, S Majumder, FA Jolesz, ... PloS one 6 (10), e25451, 2011 | 328 | 2011 |
| Outcome prediction in patients with glioblastoma by using imaging, clinical, and genomic biomarkers: focus on the nonenhancing component of the tumor R Jain, LM Poisson, D Gutman, L Scarpace, SN Hwang, CA Holder, ... Radiology 272 (2), 484-493, 2014 | 254 | 2014 |
| Safety, antitumor activity, and immune activation of pegylated recombinant human interleukin-10 (AM0010) in patients with advanced solid tumors A Naing, KP Papadopoulos, KA Autio, PA Ott, MR Patel, DJ Wong, ... Journal of Clinical Oncology 34 (29), 3562-3569, 2016 | 252 | 2016 |
| Federated learning enables big data for rare cancer boundary detection S Pati, U Baid, B Edwards, M Sheller, SH Wang, GA Reina, P Foley, ... Nature communications 13 (1), 7346, 2022 | 210 | 2022 |
| Incidence of immune-related adverse events and its association with treatment outcomes: the MD Anderson Cancer Center experience T Fujii, RR Colen, MA Bilen, KR Hess, J Hajjar, ME Suarez-Almazor, ... Investigational new drugs 36, 638-646, 2018 | 171 | 2018 |
| Imaging of liver tumors using surface-enhanced Raman scattering nanoparticles C Andreou, V Neuschmelting, DF Tschaharganeh, CH Huang, ... ACS nano 10 (5), 5015-5026, 2016 | 167 | 2016 |
| Genomic mapping and survival prediction in glioblastoma: molecular subclassification strengthened by hemodynamic imaging biomarkers R Jain, L Poisson, J Narang, D Gutman, L Scarpace, SN Hwang, C Holder, ... Radiology 267 (1), 212-220, 2013 | 154 | 2013 |
| Neurosurgical applications of MRI guided laser interstitial thermal therapy (LITT) U Salem, VA Kumar, JE Madewell, DF Schomer, DC de Almeida Bastos, ... Cancer Imaging 19, 1-13, 2019 | 150 | 2019 |
| Window-of-opportunity clinical trial of pembrolizumab in patients with recurrent glioblastoma reveals predominance of immune-suppressive macrophages J De Groot, M Penas-Prado, K Alfaro-Munoz, K Hunter, BL Pei, B O’Brien, ... Neuro-oncology 22 (4), 539-549, 2020 | 147 | 2020 |
| Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients M Nicolasjilwan, Y Hu, C Yan, D Meerzaman, CA Holder, D Gutman, ... Journal of Neuroradiology 42 (4), 212-221, 2015 | 142 | 2015 |
| Adenocarcinomas of the esophagus: response to chemoradiotherapy is associated with decrease of metabolic tumor volume as measured on PET–CT: comparison to histopathologic and … JB Roedl, RR Colen, NS Holalkere, AJ Fischman, NC Choi, MA Blake Radiotherapy and oncology 89 (3), 278-286, 2008 | 142 | 2008 |
| Multicenter study demonstrates radiomic features derived from magnetic resonance perfusion images identify pseudoprogression in glioblastoma N Elshafeey, A Kotrotsou, A Hassan, N Elshafei, I Hassan, S Ahmed, ... Nature communications 10 (1), 3170, 2019 | 138 | 2019 |
| Identifying the best machine learning algorithms for brain tumor segmentation S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... progression assessment, and overall survival prediction in the BRATS …, 2018 | 137 | 2018 |
| Phase 2 study of pembrolizumab in patients with advanced rare cancers A Naing, F Meric-Bernstam, B Stephen, DD Karp, J Hajjar, JR Ahnert, ... Journal for immunotherapy of cancer 8 (1), 2020 | 134 | 2020 |
