| Domain-specific language model pretraining for biomedical natural language processing Y Gu, R Tinn, H Cheng, M Lucas, N Usuyama, X Liu, T Naumann, J Gao, ... ACM Transactions on Computing for Healthcare (HEALTH) 3 (1), 1-23, 2021 | 2114 | 2021 |
| Llava-med: Training a large language-and-vision assistant for biomedicine in one day C Li, C Wong, S Zhang, N Usuyama, H Liu, J Yang, T Naumann, H Poon, ... Advances in Neural Information Processing Systems 36, 2024 | 604 | 2024 |
| Can generalist foundation models outcompete special-purpose tuning? case study in medicine H Nori, YT Lee, S Zhang, D Carignan, R Edgar, N Fusi, N King, J Larson, ... arXiv preprint arXiv:2311.16452, 2023 | 271 | 2023 |
| Making the most of text semantics to improve biomedical vision–language processing B Boecking, N Usuyama, S Bannur, DC Castro, A Schwaighofer, S Hyland, ... European conference on computer vision, 1-21, 2022 | 250 | 2022 |
| A whole-slide foundation model for digital pathology from real-world data H Xu, N Usuyama, J Bagga, S Zhang, R Rao, T Naumann, C Wong, ... Nature, 1-8, 2024 | 171 | 2024 |
| Large-scale domain-specific pretraining for biomedical vision-language processing S Zhang, Y Xu, N Usuyama, J Bagga, R Tinn, S Preston, R Rao, M Wei, ... arXiv preprint arXiv:2303.00915 2 (3), 6, 2023 | 161 | 2023 |
| BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs S Zhang, Y Xu, N Usuyama, H Xu, J Bagga, R Tinn, S Preston, R Rao, ... arXiv preprint arXiv:2303.00915, 2023 | 148 | 2023 |
| Fine-tuning large neural language models for biomedical natural language processing R Tinn, H Cheng, Y Gu, N Usuyama, X Liu, T Naumann, J Gao, H Poon Patterns 4 (4), 2023 | 121 | 2023 |
| Fast and accurate medication identification N Larios Delgado, N Usuyama, AK Hall, RJ Hazen, M Ma, S Sahu, ... NPJ digital medicine 2 (1), 10, 2019 | 43 | 2019 |
| Exploring the Boundaries of GPT-4 in Radiology Q Liu, S Hyland, S Bannur, K Bouzid, DC Castro, MT Wetscherek, R Tinn, ... arXiv preprint arXiv:2310.14573, 2023 | 33 | 2023 |
| HapMuC: somatic mutation calling using heterozygous germ line variants near candidate mutations N Usuyama, Y Shiraishi, Y Sato, H Kume, Y Homma, S Ogawa, S Miyano, ... Bioinformatics 30 (23), 3302-3309, 2014 | 30 | 2014 |
| Domain-specific language model pretraining for biomedical natural language processing. arXiv Y Gu, R Tinn, H Cheng, M Lucas, N Usuyama, X Liu, T Naumann, J Gao, ... preprint, 2020 | 28 | 2020 |
| Scaling clinical trial matching using large language models: a case study in oncology C Wong, S Zhang, Y Gu, C Moung, J Abel, N Usuyama, R Weerasinghe, ... Machine Learning for Healthcare Conference, 846-862, 2023 | 26 | 2023 |
| Distilling large language models for biomedical knowledge extraction: A case study on adverse drug events Y Gu, S Zhang, N Usuyama, Y Woldesenbet, C Wong, P Sanapathi, ... arXiv preprint arXiv:2307.06439, 2023 | 25 | 2023 |
| Training small multimodal models to bridge biomedical competency gap: A case study in radiology imaging JMZ Chaves, SC Huang, Y Xu, H Xu, N Usuyama, S Zhang, F Wang, ... CoRR, 2024 | 18 | 2024 |
| Biomedjourney: Counterfactual biomedical image generation by instruction-learning from multimodal patient journeys Y Gu, J Yang, N Usuyama, C Li, S Zhang, MP Lungren, J Gao, H Poon arXiv preprint arXiv:2310.10765, 2023 | 15 | 2023 |
| Domain-specific pretraining for vertical search: Case study on biomedical literature Y Wang, J Li, T Naumann, C Xiong, H Cheng, R Tinn, C Wong, ... Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 15 | 2021 |
| Domain-specific language model pretraining for biomedical natural language processing, 2020. arXiv Y Gu, R Tinn, H Cheng, M Lucas, N Usuyama, X Liu, T Naumann, J Gao, ... arXiv preprint arXiv:2007.15779, 0 | 14 | |
| When an image is worth 1,024 x 1,024 words: A case study in computational pathology W Wang, S Ma, H Xu, N Usuyama, J Ding, H Poon, F Wei arXiv preprint arXiv:2312.03558, 2023 | 13 | 2023 |
| Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision S Preston, M Wei, R Rao, R Tinn, N Usuyama, M Lucas, Y Gu, ... Patterns 4 (4), 2023 | 13 | 2023 |
