| 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 | 1365 | 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 | 424* | 2018 |
| Artificial intelligence augmentation of radiologist performance in distinguishing COVID-19 from pneumonia of other origin at chest CT HX Bai, R Wang, Z Xiong, B Hsieh, K Chang, K Halsey, TML Tran, ... Radiology 296 (3), E156-E165, 2020 | 379 | 2020 |
| Residual Convolutional Neural Network for the Determination of IDH Status in Low-and High-Grade Gliomas from MR ImagingNeural Network for Determination of IDH Status in Gliomas K Chang, HX Bai, H Zhou, C Su, WL Bi, E Agbodza, VK Kavouridis, ... Clinical Cancer Research 24 (5), 1073-1081, 2018 | 297 | 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 | 259 | 2018 |
| Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas B Zhang, K Chang, S Ramkissoon, S Tanguturi, WL Bi, DA Reardon, ... Neuro-oncology 19 (1), 109-117, 2016 | 226 | 2016 |
| Epidermal devices for noninvasive, precise, and continuous mapping of macrovascular and microvascular blood flow RC Webb, Y Ma, S Krishnan, Y Li, S Yoon, X Guo, X Feng, Y Shi, M Seidel, ... Science advances 1 (9), e1500701, 2015 | 203 | 2015 |
| Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs using Convolutional Siamese Neural Networks MD Li, NT Arun, M Gidwani, K Chang, F Deng, BP Little, DP Mendoza, ... Radiology: Artificial Intelligence 2 (4), e200079, 2020 | 135* | 2020 |
| 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 | 134 | 2018 |
| Assessing the trustworthiness of saliency maps for localizing abnormalities in medical imaging N Arun, N Gaw, P Singh, K Chang, M Aggarwal, B Chen, K Hoebel, ... Radiology: Artificial Intelligence 3 (6), 2021 | 127* | 2021 |
| 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 | 123 | 2019 |
| Federated learning for breast density classification: A real-world implementation HR Roth, K Chang, P Singh, N Neumark, W Li, V Gupta, S Gupta, L Qu, ... Domain Adaptation and Representation Transfer, and Distributed and …, 2020 | 112 | 2020 |
| Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low-and high-grade gliomas H Zhou, K Chang, HX Bai, B Xiao, C Su, WL Bi, PJ Zhang, JT Senders, ... Journal of neuro-oncology 142 (2), 299-307, 2019 | 99 | 2019 |
| Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab P Grossmann, V Narayan, K Chang, R Rahman, L Abrey, DA Reardon, ... Neuro-oncology 19 (12), 1688-1697, 2017 | 93 | 2017 |
| 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 | 89 | 2018 |
| Multimodal imaging patterns predict survival in recurrent glioblastoma patients treated with bevacizumab K Chang, B Zhang, X Guo, M Zong, R Rahman, D Sanchez, N Winder, ... Neuro-oncology 18 (12), 1680-1687, 2016 | 89 | 2016 |
| Split Learning for collaborative deep learning in healthcare MG Poirot, P Vepakomma, K Chang, J Kalpathy-Cramer, R Gupta, ... arXiv preprint arXiv:1912.12115, 2019 | 73 | 2019 |
| Sequential neural networks for biologically informed glioma segmentation A Beers, K Chang, J Brown, E Gerstner, B Rosen, J Kalpathy-Cramer Medical Imaging 2018: Image Processing 10574, 1057433, 2018 | 73* | 2018 |
| Prognostication of patients with COVID-19 using artificial intelligence based on chest x-rays and clinical data: a retrospective study Z Jiao, JW Choi, K Halsey, TML Tran, B Hsieh, D Wang, F Eweje, R Wang, ... The Lancet Digital Health 3 (5), e286-e294, 2021 | 72 | 2021 |
| Deep learning to distinguish benign from malignant renal lesions based on routine MR imaging IL Xi, Y Zhao, R Wang, M Chang, S Purkayastha, K Chang, RY Huang, ... Clinical Cancer Research 26 (8), 1944-1952, 2020 | 70 | 2020 |
Jayashree Kalpathy-CramerUniversity of Colorado在 cuanschutz.edu 的电子邮件经过验证
