Naumann, Tristan

12 publications

MLHC 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 K. Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon, Javier González Hernández

ICLR 2024 Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Odisho, Bin Yu

NeurIPSW 2023 Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making Aliyah Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Odisho, Bin Yu

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

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

ICMLW 2023 Self-Verification Improves Few-Shot Clinical Information Extraction Zelalem Gero, Chandan Singh, Hao Cheng, Tristan Naumann, Michel Galley, Jianfeng Gao, Hoifung Poon

CHIL 2022 Conference on Health, Inference, and Learning (CHIL) 2022 Gerardo Flores, George H Chen, Tom Pollard, Ayah Zirikly, Michael C Hughes, Tasmie Sarker, Joyce C Ho, Tristan Naumann

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

MLHC 2020 Clinical Collabsheets: 53 Questions to Guide a Clinical Collaboration Shems Saleh, William Boag, Lauren Erdman, Tristan Naumann

MLHC 2019 Feature Robustness in Non-Stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi

AAAI 2018 Semi-Supervised Biomedical Translation with Cycle Wasserstein Regression GANs Matthew B. A. McDermott, Tom Yan, Tristan Naumann, Nathan Hunt, Harini Suresh, Peter Szolovits, Marzyeh Ghassemi

AAAI 2015 A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data Marzyeh Ghassemi, Marco A. F. Pimentel, Tristan Naumann, Thomas Brennan, David A. Clifton, Peter Szolovits, Mengling Feng