| Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning HC Shin, HR Roth, M Gao, L Lu, Z Xu, I Nogues, J Yao, D Mollura, ... IEEE transactions on medical imaging 35 (5), 1285-1298, 2016 | 6101 | 2016 |
| The multimodal brain tumor image segmentation benchmark (BRATS) BH Menze, A Jakab, S Bauer, J Kalpathy-Cramer, K Farahani, J Kirby, ... IEEE transactions on medical imaging 34 (10), 1993-2024, 2014 | 5929 | 2014 |
| Deeporgan: Multi-level deep convolutional networks for automated pancreas segmentation HR Roth, L Lu, A Farag, HC Shin, J Liu, EB Turkbey, RM Summers Medical Image Computing and Computer-Assisted Intervention--MICCAI 2015 …, 2015 | 858 | 2015 |
| Medical image synthesis for data augmentation and anonymization using generative adversarial networks HC Shin Springer International Publishing, 2018 | 723 | 2018 |
| Stacked autoencoders for unsupervised feature learning and multiple organ detection in a pilot study using 4D patient data HC Shin, MR Orton, DJ Collins, SJ Doran, MO Leach IEEE transactions on pattern analysis and machine intelligence 35 (8), 1930-1943, 2012 | 603 | 2012 |
| Learning to read chest x-rays: Recurrent neural cascade model for automated image annotation HC Shin, K Roberts, L Lu, D Demner-Fushman, J Yao, RM Summers Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 445 | 2016 |
| A large language model for electronic health records X Yang, A Chen, N PourNejatian, HC Shin, KE Smith, C Parisien, ... NPJ digital medicine 5 (1), 194, 2022 | 348 | 2022 |
| Holistic classification of CT attenuation patterns for interstitial lung diseases via deep convolutional neural networks M Gao, U Bagci, L Lu, A Wu, M Buty, HC Shin, H Roth, GZ Papadakis, ... Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2018 | 296 | 2018 |
| Anatomy-specific classification of medical images using deep convolutional nets HR Roth, CT Lee, HC Shin, A Seff, L Kim, J Yao, L Lu, RM Summers 2015 IEEE 12th international symposium on biomedical imaging (ISBI), 101-104, 2015 | 233 | 2015 |
| Interleaved text/image deep mining on a large-scale radiology database for automated image interpretation HC Shin, L Lu, L Kim, A Seff, J Yao, RM Summers Journal of Machine Learning Research 17 (107), 1-31, 2016 | 216 | 2016 |
| BioMegatron: larger biomedical domain language model HC Shin, Y Zhang, E Bakhturina, R Puri, M Patwary, M Shoeybi, R Mani Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 132 | 2020 |
| International conference on medical image computing and computer-assisted intervention HR Roth, L Lu, A Farag, HC Shin, J Liu, EB Turkbey, RM Summers Springer, 2017 | 105 | 2017 |
| Gatortron: A large clinical language model to unlock patient information from unstructured electronic health records X Yang, A Chen, N PourNejatian, HC Shin, KE Smith, C Parisien, ... arXiv preprint arXiv:2203.03540, 2022 | 69 | 2022 |
| Leveraging mid-level semantic boundary cues for automated lymph node detection A Seff, L Lu, A Barbu, H Roth, HC Shin, RM Summers Medical Image Computing and Computer-Assisted Intervention--MICCAI 2015 …, 2015 | 46 | 2015 |
| Unsupervised joint mining of deep features and image labels for large-scale radiology image categorization and scene recognition X Wang, L Lu, HC Shin, L Kim, M Bagheri, I Nogues, J Yao, RM Summers 2017 IEEE Winter Conference on Applications of Computer Vision (WACV), 998-1007, 2017 | 45 | 2017 |
| Autoencoder in time-series analysis for unsupervised tissues characterisation in a large unlabelled medical image dataset HC Shin, M Orton, DJ Collins, S Doran, MO Leach 2011 10th international conference on machine learning and applications and …, 2011 | 39 | 2011 |
| Hybrid clustering and logistic regression for multi-modal brain tumor segmentation HC Shin Proc. of Workshops and Challanges in Medical Image Computing and Computer …, 2012 | 38 | 2012 |
| Ganbert: Generative adversarial networks with bidirectional encoder representations from transformers for mri to pet synthesis HC Shin, A Ihsani, S Mandava, ST Sreenivas, C Forster, J Cha, ... arXiv preprint arXiv:2008.04393, 2020 | 24 | 2020 |
| GANDALF: Generative adversarial networks with discriminator-adaptive loss fine-tuning for Alzheimer’s disease diagnosis from MRI HC Shin, A Ihsani, Z Xu, S Mandava, ST Sreenivas, C Forster, J Cha, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020 | 24 | 2020 |
| The potential dangers of artificial intelligence for radiology and radiologists LC Chu, A Anandkumar, HC Shin, EK Fishman Journal of the American College of Radiology 17 (10), 1309-1311, 2020 | 23 | 2020 |
Le LuAlibaba DAMO Academy, IEEE Fellow, MICCAI Board Member (2021-2024)Verified email at alibaba-inc.com
