| Radiomic features from the peritumoral brain parenchyma on treatment-naive multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme … P Prasanna, J Patel, S Partovi, A Madabhushi, P Tiwari European radiology 27, 4188-4197, 2017 | 300 | 2017 |
| 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), e200267, 2021 | 258 | 2021 |
| 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 | 221 | 2020 |
| Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma N Beig, J Patel, P Prasanna, V Hill, A Gupta, R Correa, K Bera, S Singh, ... Scientific reports 8 (1), 7, 2018 | 126 | 2018 |
| Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors J Peng, DD Kim, JB Patel, X Zeng, J Huang, K Chang, X Xun, C Zhang, ... Neuro-oncology 24 (2), 289-299, 2022 | 56 | 2022 |
| 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 | 56 | 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 | 55 | 2019 |
| QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation-analysis of ranking scores and benchmarking results R Mehta, A Filos, U Baid, C Sako, R McKinley, M Rebsamen, K Dätwyler, ... The journal of machine learning for biomedical imaging 2022, 2022 | 51 | 2022 |
| 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 | 51 | 2020 |
| 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 | 50 | 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 | 47 | 2020 |
| Assessing the validity of saliency maps for abnormality localization in medical imaging NT Arun, N Gaw, P Singh, K Chang, KV Hoebel, J Patel, M Gidwani, ... arXiv preprint arXiv:2006.00063, 2020 | 27 | 2020 |
| Mass effect deformation heterogeneity (MEDH) on gadolinium-contrast T1-weighted MRI is associated with decreased survival in patients with right cerebral hemisphere … P Prasanna, J Mitra, N Beig, A Nayate, J Patel, S Ghose, R Thawani, ... Scientific reports 9 (1), 1145, 2019 | 26 | 2019 |
| Machine learning for adrenal gland segmentation and classification of normal and adrenal masses at CT C Robinson-Weiss, J Patel, BC Bizzo, DI Glazer, CP Bridge, KP Andriole, ... Radiology 306 (2), e220101, 2022 | 25 | 2022 |
| Cerebrovascular Disease Progression in Patients With ACTA2 Arg179 Pathogenic Variants A Lauer, SL Speroni, JB Patel, E Regalado, M Choi, E Smith, ... Neurology 96 (4), e538-e552, 2021 | 23 | 2021 |
| Inconsistent partitioning and unproductive feature associations yield idealized radiomic models M Gidwani, K Chang, JB Patel, KV Hoebel, SR Ahmed, P Singh, CD Fuller, ... Radiology 307 (1), e220715, 2022 | 22 | 2022 |
| Addressing catastrophic forgetting for medical domain expansion S Gupta, P Singh, K Chang, L Qu, M Aggarwal, N Arun, A Vaswani, ... arXiv preprint arXiv:2103.13511, 2021 | 20 | 2021 |
| Radiogenomic analysis of hypoxia pathway reveals computerized MRI descriptors predictive of overall survival in glioblastoma N Beig, J Patel, P Prasanna, S Partovi, V Varadan, A Madabhushi, ... Medical Imaging 2017: Computer-Aided Diagnosis 10134, 476-485, 2017 | 18 | 2017 |
| Segmentation, survival prediction, and uncertainty estimation of gliomas from multimodal 3D MRI using selective kernel networks J Patel, K Chang, K Hoebel, M Gidwani, N Arun, S Gupta, M Aggarwal, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2021 | 13 | 2021 |
| FDU-net: deep learning-based three-dimensional diffuse optical image reconstruction B Deng, H Gu, H Zhu, K Chang, KV Hoebel, JB Patel, J Kalpathy-Cramer, ... IEEE Transactions on Medical Imaging 42 (8), 2439-2450, 2023 | 12 | 2023 |
