| Minerva: Enabling low-power, highly-accurate deep neural network accelerators B Reagen, P Whatmough, R Adolf, S Rama, H Lee, SK Lee, ... ACM SIGARCH Computer Architecture News 44 (3), 267-278, 2016 | 745 | 2016 |
| Fully automated deep learning system for bone age assessment H Lee, S Tajmir, J Lee, M Zissen, BA Yeshiwas, TK Alkasab, G Choy, ... Journal of digital imaging 30, 427-441, 2017 | 456 | 2017 |
| An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets H Lee, S Yune, M Mansouri, M Kim, SH Tajmir, CE Guerrier, SA Ebert, ... Nature biomedical engineering 3 (3), 173-182, 2019 | 420 | 2019 |
| 14.3 A 28nm SoC with a 1.2 GHz 568nJ/prediction sparse deep-neural-network engine with> 0.1 timing error rate tolerance for IoT applications PN Whatmough, SK Lee, H Lee, S Rama, D Brooks, GY Wei 2017 IEEE International Solid-State Circuits Conference (ISSCC), 242-243, 2017 | 207 | 2017 |
| Pixel-level deep segmentation: artificial intelligence quantifies muscle on computed tomography for body morphometric analysis H Lee, FM Troschel, S Tajmir, G Fuchs, J Mario, FJ Fintelmann, S Do Journal of digital imaging 30, 487-498, 2017 | 160 | 2017 |
| Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability SH Tajmir, H Lee, R Shailam, HI Gale, JC Nguyen, SJ Westra, R Lim, ... Skeletal radiology 48, 275-283, 2019 | 108 | 2019 |
| Urinary stone detection on CT images using deep convolutional neural networks: evaluation of model performance and generalization A Parakh, H Lee, JH Lee, BH Eisner, DV Sahani, S Do Radiology: Artificial Intelligence 1 (4), e180066, 2019 | 107 | 2019 |
| A deep-learning system for fully-automated peripherally inserted central catheter (PICC) tip detection H Lee, M Mansouri, S Tajmir, MH Lev, S Do Journal of digital imaging 31, 393-402, 2018 | 58 | 2018 |
| Machine friendly machine learning: interpretation of computed tomography without image reconstruction H Lee, C Huang, S Yune, SH Tajmir, M Kim, S Do Scientific reports 9 (1), 15540, 2019 | 51 | 2019 |
| Beyond human perception: sexual dimorphism in hand and wrist radiographs is discernible by a deep learning model S Yune, H Lee, M Kim, SH Tajmir, MS Gee, S Do Journal of Digital Imaging 32, 665-671, 2019 | 37 | 2019 |
| Systems, methods and media for automatically generating a bone age assessment from a radiograph S Do, H Lee, M Gee, S Tajmir, T Alkasab US Patent 10,991,093, 2021 | 36 | 2021 |
| Practical window setting optimization for medical image deep learning H Lee, M Kim, S Do arXiv preprint arXiv:1812.00572, 2018 | 34 | 2018 |
| Towards generative adversarial networks as a new paradigm for radiology education SG Finlayson, H Lee, IS Kohane, L Oakden-Rayner arXiv preprint arXiv:1812.01547, 2018 | 21 | 2018 |
| A multi-chip system optimized for insect-scale flapping-wing robots X Zhang, M Lok, T Tong, S Chaput, SK Lee, B Reagen, H Lee, D Brooks, ... 2015 Symposium on VLSI Circuits (VLSI Circuits), C152-C153, 2015 | 18 | 2015 |
| Pattern recognition in musculoskeletal imaging using artificial intelligence N Gorelik, J Chong, DJ Lin Seminars in musculoskeletal radiology 24 (01), 38-49, 2020 | 13 | 2020 |
| Machine learning powered automatic organ classification for patient specific organ dose estimation J Cho, E Lee, H Lee, B Liu, X Li, S Tajmir, D Sahani, S Do Proceedings of the Society for Imaging Informatics in Medicine Annual Meeting, 2017 | 8 | 2017 |
| Impact of a categorical AI system for digital breast tomosynthesis on breast cancer interpretation by both general radiologists and breast imaging specialists JG Kim, B Haslam, AR Diab, A Sakhare, G Grisot, H Lee, J Holt, CI Lee, ... Radiology: Artificial Intelligence 6 (2), e230137, 2024 | 3 | 2024 |
| Generalizable and Explainable Deep Learning in Medical Imaging with Small Data H Lee Harvard University, 2020 | 1 | 2020 |
| CASE-BASED LEARNING BASED ON ARTIFICIAL INTELLIGENCE RADIOLOGY ATLAS: EXAMPLE OF INTRACRANIAL HEMORRHAGE AND URINARY STONE DETECTION S Yune, H Lee, S Do, D Ting JOURNAL OF GENERAL INTERNAL MEDICINE 33, S685-S686, 2018 | 1 | 2018 |
| System and method for analyzing medical images to detect and classify a medical condition using machine-learning and a case pertinent radiology atlas H Lee, S Yune, S Do US Patent 11,972,567, 2024 | | 2024 |
