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)

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)

TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models. - Javier González Hernández; Cliff Wong; Zelalem Gero; Jass Bagga; Risa Ueno; Isabel Chien; Eduard Oravkin; Emre Kiciman; Aditya V. Nori; Roshanthi Weerasinghe; Rom S. Leidner; Brian Piening; et al. (CoRR, 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)

Applying Large Language Models for Causal Structure Learning in Non Small Cell Lung Cancer. - Narmada Naik; Ayush Khandelwal; Mohit Joshi; Madhusudan Atre; Hollis Wright; Kavya Kannan; Scott Hill; Giridhar Mamidipudi; Ganapati Srinivasa; Carlo Bifulco; Brian Piening; Kevin Matlock (ICHI, 2024)

Beyond Clinical Trials: Using Real World Evidence to Investigate Heterogeneous, Time-Varying Treatment Effects. - Isabel Chien; Cliff Wong; Zelalem Gero; Jaspreet Bagga; Risa Ueno; Richard E. Turner; Roshanthi Weerasinghe; Brian Piening; Tristan Naumann; Carlo Bifulco; Hoifung Poon; Javier González Hernández (MLHC, 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)

Multi-modal AI for comprehensive breast cancer prognostication. - Jan Witowski; Ken Zeng; Joseph Cappadona; Jailan Elayoubi; Elena Diana Chiru; Nancy Chan; Young-Joon Kang; Frederick Howard; Irina Ostrovnaya; Carlos Fernandez-Granda; Freya Schnabel; Ugur Ozerdem; et al. (CoRR, 2024)

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale. - Cliff Wong; Sam Preston; Qianchu Liu; Zelalem Gero; Jass Bagga; Sheng Zhang 012; Shrey Jain; Theodore Zhao; Yu Gu 017; Yanbo Xu; Sid Kiblawi; Roshanthi Weerasinghe; et al. (CoRR, 2025)