| Differential data augmentation techniques for medical imaging classification tasks Z Hussain, F Gimenez, D Yi, D Rubin AMIA annual symposium proceedings 2017, 979, 2017 | 448 | 2017 |
| Automated detection of diabetic retinopathy using deep learning C Lam, D Yi, M Guo, T Lindsey AMIA summits on translational science proceedings 2018, 147, 2018 | 390 | 2018 |
| Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms T Schaffter, DSM Buist, CI Lee, Y Nikulin, D Ribli, Y Guan, W Lotter, Z Jie, ... JAMA network open 3 (3), e200265-e200265, 2020 | 348 | 2020 |
| 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 | 334 | 2018 |
| Assessment of convolutional neural networks for automated classification of chest radiographs JA Dunnmon, D Yi, CP Langlotz, C Ré, DL Rubin, MP Lungren Radiology 290 (2), 537-544, 2019 | 221 | 2019 |
| Deep learning enables automatic detection and segmentation of brain metastases on multisequence MRI E Grøvik, D Yi, M Iv, E Tong, D Rubin, G Zaharchuk Journal of Magnetic Resonance Imaging 51 (1), 175-182, 2020 | 214 | 2020 |
| CT-ORG, a new dataset for multiple organ segmentation in computed tomography B Rister, D Yi, K Shivakumar, T Nobashi, DL Rubin Scientific Data 7 (1), 381, 2020 | 104 | 2020 |
| 3-D convolutional neural networks for glioblastoma segmentation D Yi, M Zhou, Z Chen, O Gevaert arXiv preprint arXiv:1611.04534, 2016 | 65 | 2016 |
| Optimizing and visualizing deep learning for benign/malignant classification in breast tumors D Yi, RL Sawyer, D Cohn III, J Dunnmon, C Lam, X Xiao, D Rubin arXiv preprint arXiv:1705.06362, 2017 | 56 | 2017 |
| A critical-like collective state leads to long-range cell communication in Dictyostelium discoideum aggregation G De Palo, D Yi, RG Endres PLoS biology 15 (4), e1002602, 2017 | 43 | 2017 |
| Handling missing MRI sequences in deep learning segmentation of brain metastases: a multicenter study E Grøvik, D Yi, M Iv, E Tong, LB Nilsen, A Latysheva, C Saxhaug, ... NPJ digital medicine 4 (1), 33, 2021 | 42 | 2021 |
| Deep Learning for abnormality detection in Chest X-Ray images C Tataru, D Yi, A Shenoyas, A Ma IEEE conference on deep learning, 2017 | 36 | 2017 |
| The game imitation: Deep supervised convolutional networks for quick video game AI Z Chen, D Yi arXiv preprint arXiv:1702.05663, 2017 | 27 | 2017 |
| Evaluation of artificial intelligence–based intraoperative guidance tools for phacoemulsification cataract surgery RG Nespolo, D Yi, E Cole, N Valikodath, C Luciano, YI Leiderman JAMA ophthalmology 140 (2), 170-177, 2022 | 23 | 2022 |
| Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms. JAMA Netw Open. 2020; 3 (3): e200265 T Schaffter, DSM Buist, CI Lee, Y Nikulin, D Ribli, Y Guan, W Lotter, Z Jie, ... | 21 | 2020 |
| 2.5 D and 3D segmentation of brain metastases with deep learning on multinational MRI data JA Ottesen, D Yi, E Tong, M Iv, A Latysheva, C Saxhaug, KD Jacobsen, ... Frontiers in Neuroinformatics 16, 1056068, 2023 | 15 | 2023 |
| MRI pulse sequence integration for deep‐learning‐based brain metastases segmentation D Yi, E Grøvik, E Tong, M Iv, KE Emblem, LB Nilsen, C Saxhaug, ... Medical Physics 48 (10), 6020-6035, 2021 | 13 | 2021 |
| CT organ segmentation using GPU data augmentation, unsupervised labels and IOU loss B Rister, D Yi, K Shivakumar, T Nobashi, DL Rubin arXiv preprint arXiv:1811.11226, 2018 | 10 | 2018 |
| Systems and Methods for Clinical Image Classification D Yi, TC Chang, JC Liao, DL Rubin US Patent App. 15/917,494, 2018 | 10 | 2018 |
| DeepPerimeter: Indoor boundary estimation from posed monocular sequences A Phalak, Z Chen, D Yi, K Gupta, V Badrinarayanan, A Rabinovich arXiv preprint arXiv:1904.11595, 2019 | 9 | 2019 |
