| 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 | 2069 | 2018 |
| Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks JM Brown, JP Campbell, A Beers, K Chang, S Ostmo, RVP Chan, J Dy, ... JAMA ophthalmology 136 (7), 803-810, 2018 | 611* | 2018 |
| Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging K Chang, HX Bai, H Zhou, C Su, WL Bi, E Agbodza, VK Kavouridis, ... Clinical Cancer Research 24 (5), 1073-1081, 2018 | 398 | 2018 |
| Distributed deep learning networks among institutions for medical imaging K Chang, N Balachandar, C Lam, D Yi, J Brown, A Beers, B Rosen, ... Journal of the American Medical Informatics Association 25 (8), 945-954, 2018 | 364 | 2018 |
| Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement K Chang, AL Beers, HX Bai, JM Brown, KI Ly, X Li, JT Senders, ... Neuro-oncology 21 (11), 1412-1422, 2019 | 188 | 2019 |
| ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI S Winzeck, A Hakim, R McKinley, JA Pinto, V Alves, C Silva, M Pisov, ... Frontiers in neurology 9, 679, 2018 | 177 | 2018 |
| High-resolution medical image synthesis using progressively grown generative adversarial networks A Beers, J Brown, K Chang, JP Campbell, S Ostmo, MF Chiang, ... arXiv preprint arXiv:1805.03144, 2018 | 132 | 2018 |
| Combining interventions to reduce the spread of viral misinformation JB Bak-Coleman, I Kennedy, M Wack, A Beers, JS Schafer, ES Spiro, ... Nature Human Behaviour 6 (10), 1372-1380, 2022 | 113 | 2022 |
| Sequential 3d u-nets for biologically-informed brain tumor segmentation A Beers, K Chang, J Brown, E Sartor, CP Mammen, E Gerstner, B Rosen, ... arXiv preprint arXiv:1709.02967, 2017 | 91* | 2017 |
| Automated fundus image quality assessment in retinopathy of prematurity using deep convolutional neural networks AS Coyner, R Swan, JP Campbell, S Ostmo, JM Brown, ... Ophthalmology retina 3 (5), 444-450, 2019 | 67 | 2019 |
| Bevacizumab reduces permeability and concurrent temozolomide delivery in a subset of patients with recurrent glioblastoma ER Gerstner, KE Emblem, K Chang, B Vakulenko-Lagun, YF Yen, ... Clinical Cancer Research 26 (1), 206-212, 2020 | 64 | 2020 |
| DeepNeuro: an open-source deep learning toolbox for neuroimaging A Beers, J Brown, K Chang, K Hoebel, J Patel, KI Ly, SM Tolaney, ... Neuroinformatics 19, 127-140, 2021 | 55 | 2021 |
| Machine learning models can detect aneurysm rupture and identify clinical features associated with rupture MA Silva, J Patel, V Kavouridis, T Gallerani, A Beers, K Chang, KV Hoebel, ... World Neurosurgery 131, e46-e51, 2019 | 54 | 2019 |
| Radiomics repeatability pitfalls in a scan-rescan MRI study of glioblastoma KV Hoebel, JB Patel, AL Beers, K Chang, P Singh, JM Brown, MC Pinho, ... Radiology: Artificial Intelligence 3 (1), e190199, 2020 | 49 | 2020 |
| Multi-institutional assessment and crowdsourcing evaluation of deep learning for automated classification of breast density K Chang, AL Beers, L Brink, JB Patel, P Singh, NT Arun, KV Hoebel, ... Journal of the American College of Radiology 17 (12), 1653-1662, 2020 | 49 | 2020 |
| An exploration of uncertainty information for segmentation quality assessment K Hoebel, V Andrearczyk, A Beers, J Patel, K Chang, A Depeursinge, ... Medical Imaging 2020: Image Processing 11313, 381-390, 2020 | 46 | 2020 |
| Semi-supervised deep learning for abnormality classification in retinal images B Lecouat, K Chang, CS Foo, B Unnikrishnan, JM Brown, H Zenati, ... arXiv preprint arXiv:1812.07832, 2018 | 43 | 2018 |
| Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning JM Brown, JP Campbell, A Beers, K Chang, K Donohue, S Ostmo, ... Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and …, 2018 | 41 | 2018 |
| Evaluating multisite rCBV consistency from DSC-MRI imaging protocols and postprocessing software across the NCI quantitative imaging network sites using a digital reference … LC Bell, N Semmineh, H An, C Eldeniz, R Wahl, KM Schmainda, MA Prah, ... Tomography 5 (1), 110, 2019 | 35 | 2019 |
| A multi-institutional comparison of dynamic contrast-enhanced magnetic resonance imaging parameter calculations Scientific reports 7 (1), 11185, 2017 | 35* | 2017 |
