HapMuC: somatic mutation calling using heterozygous germ line variants near candidate mutations. - Naoto Usuyama; Yuichi Shiraishi; Yusuke Sato; Haruki Kume; Yukio Homma; Seishi Ogawa; Satoru Miyano; Seiya Imoto (Bioinform., 2014)

Fast and accurate medication identification. - Natalia Larios Delgado; Naoto Usuyama; Amanda K. Hall; Rebecca J. Hazen; Max Ma; Siva Sahu; Jessica Lundin (npj Digit. Medicine, 2019)

ePillID Dataset: A Low-Shot Fine-Grained Benchmark for Pill Identification. - Naoto Usuyama; Natalia Larios Delgado; Amanda K. Hall; Jessica Lundin (CVPR Workshops, 2020)

Modular Self-Supervision for Document-Level Relation Extraction. - Sheng Zhang 012; Cliff Wong; Naoto Usuyama; Sarthak Jain; Tristan Naumann; Hoifung Poon (EMNLP (1), 2021)

Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature. - Yu Wang 009; Jinchao Li; Tristan Naumann; Chenyan Xiong; Hao Cheng 002; Robert Tinn; Cliff Wong; Naoto Usuyama; Richard Rogahn; Zhihong Shen; Yang Qin; Eric Horvitz; et al. (KDD, 2021)

Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. - Benedikt Boecking; Naoto Usuyama; Shruthi Bannur; Daniel C. Castro; Anton Schwaighofer; Stephanie L. Hyland; Maria Wetscherek; Tristan Naumann; Aditya V. Nori; Javier Alvarez-Valle; Hoifung Poon; Ozan Oktay (ECCV (36), 2022)

Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision. - Sam Preston; Mu Wei; Rajesh Rao; Robert Tinn; Naoto Usuyama; Michael Lucas; Roshanthi Weerasinghe; Soohee Lee; Brian Piening; Paul Tittel; Naveen Valluri; Tristan Naumann; et al. (CoRR, 2022)

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. - Yu Gu 017; Robert Tinn; Hao Cheng 002; Michael Lucas; Naoto Usuyama; Xiaodong Liu 003; Tristan Naumann; Jianfeng Gao 001; Hoifung Poon (ACM Trans. Comput. Heal., 2022)

Exploring the Boundaries of GPT-4 in Radiology. - Qianchu Liu; Stephanie L. Hyland; Shruthi Bannur; Kenza Bouzid; Daniel C. Castro; Maria Wetscherek; Robert Tinn; Harshita Sharma; Fernando Pérez-García; Anton Schwaighofer; Pranav Rajpurkar; Sameer Tajdin Khanna; et al. (EMNLP, 2023)

Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology. - Cliff Wong; Sheng Zhang 012; Yu Gu 017; Christine Moung; Jacob Abel; Naoto Usuyama; Roshanthi Weerasinghe; Brian Piening; Tristan Naumann; Carlo Bifulco; Hoifung Poon (MLHC, 2023)

LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. - Chunyuan Li; Cliff Wong; Sheng Zhang 012; Naoto Usuyama; Haotian Liu; Jianwei Yang; Tristan Naumann; Hoifung Poon; Jianfeng Gao 001 (NeurIPS, 2023)

Large-Scale Domain-Specific Pretraining for Biomedical Vision-Language Processing. - Sheng Zhang 012; Yanbo Xu; Naoto Usuyama; Jaspreet Bagga; Robert Tinn; Sam Preston; Rajesh Rao; Mu Wei; Naveen Valluri; Cliff Wong; Matthew P. Lungren; Tristan Naumann; et al. (CoRR, 2023)

Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events. - Yu Gu 017; Sheng Zhang 012; Naoto Usuyama; Yonas Woldesenbet; Cliff Wong; Praneeth Sanapathi; Mu Wei; Naveen Valluri; Erika Strandberg; Tristan Naumann; Hoifung Poon (CoRR, 2023)

BiomedJourney: Counterfactual Biomedical Image Generation by Instruction-Learning from Multimodal Patient Journeys. - Yu Gu 017; Jianwei Yang; Naoto Usuyama; Chunyuan Li; Sheng Zhang 012; Matthew P. Lungren; Jianfeng Gao 001; Hoifung Poon (CoRR, 2023)

Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine. - Harsha Nori; Yin Tat Lee; Sheng Zhang 012; Dean Carignan; Richard Edgar; Nicolò Fusi; Nicholas King; Jonathan Larson; Yuanzhi Li; Weishung Liu; Renqian Luo; Scott Mayer McKinney; et al. (CoRR, 2023)

When an Image is Worth 1, 024 x 1, 024 Words: A Case Study in Computational Pathology. - Wenhui Wang 003; Shuming Ma; Hanwen Xu; Naoto Usuyama; Jiayu Ding; Hoifung Poon; Furu Wei (CoRR, 2023)

Compositional Zero-Shot Domain Transfer with Text-to-Text Models. - Fangyu Liu 001; Qianchu Liu; Shruthi Bannur; Fernando Pérez-García; Naoto Usuyama; Sheng Zhang 012; Tristan Naumann; Aditya V. Nori; Hoifung Poon; Javier Alvarez-Valle; Ozan Oktay; Stephanie L. Hyland (Trans. Assoc. Comput. Linguistics, 2023)

Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision. - Sam Preston; Mu Wei; Rajesh Rao; Robert Tinn; Naoto Usuyama; Michael Lucas; Yu Gu 017; Roshanthi Weerasinghe; Soohee Lee; Brian Piening; Paul Tittel; Naveen Valluri; et al. (Patterns, 2023)

Fine-tuning large neural language models for biomedical natural language processing. - Robert Tinn; Hao Cheng 002; Yu Gu 017; Naoto Usuyama; Xiaodong Liu 003; Tristan Naumann; Jianfeng Gao 001; Hoifung Poon (Patterns, 2023)

Foundation Models for Biomedical Image Segmentation: A Survey. - Ho Hin Lee; Yu Gu 017; Theodore Zhao; Yanbo Xu; Jianwei Yang; Naoto Usuyama; Cliff Wong; Mu Wei; Bennett A. Landman; Yuankai Huo; Alberto Santamaría-Pang; Hoifung Poon (CoRR, 2024)

Training Small Multimodal Models to Bridge Biomedical Competency Gap: A Case Study in Radiology Imaging. - Juan Manuel Zambrano Chaves; Shih-Cheng Huang; Yanbo Xu; Hanwen Xu; Naoto Usuyama; Sheng Zhang 012; Fei Wang 060; Yujia Xie; Mahmoud Khademi; Ziyi Yang; Hany Hassan Awadalla; Julia Gong; et al. (CoRR, 2024)

BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once. - Theodore Zhao; Yu Gu 017; Jianwei Yang; Naoto Usuyama; Ho Hin Lee; Tristan Naumann; Jianfeng Gao 001; Angela Crabtree; Jacob Abel; Christine Moung; Brian Piening; Carlo Bifulco; et al. (CoRR, 2024)

From Medprompt to o1: Exploration of Run-Time Strategies for Medical Challenge Problems and Beyond. - Harsha Nori; Naoto Usuyama; Nicholas King; Scott Mayer McKinney; Xavier Fernandes; Sheng Zhang 012; Eric Horvitz (CoRR, 2024)

Boltzmann Attention Sampling for Image Analysis with Small Objects. - Theodore Zhao; Sid Kiblawi; Naoto Usuyama; Ho Hin Lee; Sam Preston; Hoifung Poon; Mu Wei (CVPR, 2025)

Exploring Scaling Laws for EHR Foundation Models. - Sheng Zhang 012; Qin Liu 010; Naoto Usuyama; Cliff Wong; Tristan Naumann; Hoifung Poon (CoRR, 2025)

Generative Medical Event Models Improve with Scale. - Shane Waxler; Paul Blazek; Davis White; Daniel Sneider; Kevin Chung; Mani Nagarathnam; Patrick Williams; Hank Voeller; Karen Wong; Matthew Swanhorst; Sheng Zhang 012; Naoto Usuyama; et al. (CoRR, 2025)