Tristan Naumann

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 61

Top Venues

Massachusetts Institute of Technology, Cambridge, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, USA

PHD

Publications

Theodore Zhao, Yu Gu, Jianwei Yang, Naoto Usuyama, Ho Hin Lee, Tristan Naumann, Jianfeng Gao, Angela Crabtree, Jacob Abel, Christine Moung, Brian Piening, Carlo Bifulco, Mu Wei, Hoifung Poon, Sheng Wang
BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once. CoRR (2024)
Yiqing Xie, Sheng Zhang, Hao Cheng, Pengfei Liu, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon, Carolyn P. Rosé
DocLens: Multi-aspect Fine-grained Medical Text Evaluation. ACL (1) (2024)
Zelalem Gero, Chandan Singh, Yiqing Xie, Sheng Zhang, Tristan Naumann, Jianfeng Gao, Hoifung Poon
Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries. CoRR (2024)
Juan Manuel Zambrano Chaves, Shih-Cheng Huang, Yanbo Xu, Hanwen Xu, Naoto Usuyama, Sheng Zhang, Fei Wang, Yujia Xie, Mahmoud Khademi, Ziyi Yang, Hany Hassan Awadalla, Julia Gong, Houdong Hu, Jianwei Yang, Chunyuan Li, Jianfeng Gao, Yu Gu, Cliff Wong, Mu Wei, Tristan Naumann, Muhao Chen, Matthew P. Lungren, Serena Yeung-Levy, Curtis P. Langlotz, Sheng Wang, Hoifung Poon
Training Small Multimodal Models to Bridge Biomedical Competency Gap: A Case Study in Radiology Imaging. CoRR (2024)
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai "Orson" Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gürsoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR (2024)
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu
Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making. ICLR (2024)
Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology. CoRR (2023)
Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. NeurIPS (2023)
Griffin Adams, Bichlien H. Nguyen, Jake Smith, Yingce Xia, Shufang Xie, Anna Ostropolets, Budhaditya Deb, Yuan-Jyue Chen, Tristan Naumann, Noémie Elhadad
What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization. CoRR (2023)
Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu
An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification. CoRR (2023)
Yiqing Xie, Sheng Zhang, Hao Cheng, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon
Enhancing Medical Text Evaluation with GPT-4. CoRR (2023)
Sam Preston, Mu Wei, Rajesh Rao, Robert Tinn, Naoto Usuyama, Michael Lucas, Yu Gu, Roshanthi Weerasinghe, Soohee Lee, Brian Piening, Paul Tittel, Naveen Valluri, Tristan Naumann, Carlo Bifulco, Hoifung Poon
Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision. Patterns 4 (4) (2023)
Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. CoRR (2023)
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, Tristan Naumann, Carlo Bifulco, Hoifung Poon
TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models. CoRR (2023)
Keming Lu, Peter Potash, Xihui Lin, Yuwen Sun, Zihan Qian, Zheng Yuan, Tristan Naumann, Tianxi Cai, Junwei Lu
Prompt Discriminative Language Models for Domain Adaptation. ClinicalNLP@ACL (2023)
Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya V. Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland
Compositional Zero-Shot Domain Transfer with Text-to-Text Models. CoRR (2023)
Griffin Adams, Bichlien Nguyen, Jake Smith, Yingce Xia, Shufang Xie, Anna Ostropolets, Budhaditya Deb, Yuan-Jyue Chen, Tristan Naumann, Noémie Elhadad
What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization. ACL (1) (2023)
Sheng Zhang, Yanbo Xu, Naoto Usuyama, Jaspreet Bagga, Robert Tinn, Sam Preston, Rajesh Rao, Mu Wei, Naveen Valluri, Cliff Wong, Matthew P. Lungren, Tristan Naumann, Hoifung Poon
Large-Scale Domain-Specific Pretraining for Biomedical Vision-Language Processing. CoRR (2023)
Fangyu Liu, Qianchu Liu, Shruthi Bannur, Fernando Pérez-García, Naoto Usuyama, Sheng Zhang, Tristan Naumann, Aditya V. Nori, Hoifung Poon, Javier Alvarez-Valle, Ozan Oktay, Stephanie L. Hyland
Compositional Zero-Shot Domain Transfer with Text-to-Text Models. Trans. Assoc. Comput. Linguistics 11 (2023)
Wenxuan Zhou, Sheng Zhang, Tristan Naumann, Muhao Chen, Hoifung Poon
Continual Contrastive Finetuning Improves Low-Resource Relation Extraction. ACL (1) (2023)
Robert Tinn, Hao Cheng, Yu Gu, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
Fine-tuning large neural language models for biomedical natural language processing. Patterns 4 (4) (2023)
Yu Gu, Sheng Zhang, Naoto Usuyama, Yonas Woldesenbet, Cliff Wong, Praneeth Sanapathi, Mu Wei, Naveen Valluri, Erika Strandberg, Tristan Naumann, Hoifung Poon
Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events. CoRR (2023)
Zelalem Gero, Chandan Singh, Hao Cheng, Tristan Naumann, Michel Galley, Jianfeng Gao, Hoifung Poon
Self-Verification Improves Few-Shot Clinical Information Extraction. CoRR (2023)
Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology. MLHC (2023)
Hoifung Poon, Tristan Naumann, Sheng Zhang, Javier González Hernández
Precision Health in the Age of Large Language Models. KDD (2023)
Gerardo Flores, George H. Chen, Tom J. Pollard, Ayah Zirikly, Michael C. Hughes, Tasmie Sarker, Joyce C. Ho, Tristan Naumann
Conference on Health, Inference, and Learning (CHIL) 2022. CHIL (2022)
Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
Knowledge-Rich Self-Supervision for Biomedical Entity Linking. EMNLP (Findings) (2022)
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
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. ECCV (36) (2022)
Sam Preston, Mu Wei, Rajesh Rao, Robert Tinn, Naoto Usuyama, Michael Lucas, Roshanthi Weerasinghe, Soohee Lee, Brian Piening, Paul Tittel, Naveen Valluri, Tristan Naumann, Carlo Bifulco, Hoifung Poon
Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision. CoRR (2022)
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
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. CoRR (2022)
Wenxuan Zhou, Sheng Zhang, Tristan Naumann, Muhao Chen, Hoifung Poon
Continual Contrastive Finetuning Improves Low-Resource Relation Extraction. CoRR (2022)
Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. ACM Trans. Comput. Heal. 3 (1) (2022)
Gerardo Flores, George H. Chen, Tom J. Pollard, Joyce C. Ho, Tristan Naumann
A collection of invited non-archival papers for the Conference on Health, Inference, and Learning (CHIL) 2022. CoRR (2022)
Yu Wang, Jinchao Li, Tristan Naumann, Chenyan Xiong, Hao Cheng, Robert Tinn, Cliff Wong, Naoto Usuyama, Richard Rogahn, Zhihong Shen, Yang Qin, Eric Horvitz, Paul N. Bennett, Jianfeng Gao, Hoifung Poon
Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature. KDD (2021)
Sheng Zhang, Cliff Wong, Naoto Usuyama, Sarthak Jain, Tristan Naumann, Hoifung Poon
Modular Self-Supervision for Document-Level Relation Extraction. CoRR (2021)
Yu Wang, Jinchao Li, Tristan Naumann, Chenyan Xiong, Hao Cheng, Robert Tinn, Cliff Wong, Naoto Usuyama, Richard Rogahn, Zhihong Shen, Yang Qin, Eric Horvitz, Paul N. Bennett, Jianfeng Gao, Hoifung Poon
Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature. CoRR (2021)
Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
Knowledge-Rich Self-Supervised Entity Linking. CoRR (2021)
Robert Tinn, Hao Cheng, Yu Gu, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
Fine-Tuning Large Neural Language Models for Biomedical Natural Language Processing. CoRR (2021)
Sheng Zhang, Cliff Wong, Naoto Usuyama, Sarthak Jain, Tristan Naumann, Hoifung Poon
Modular Self-Supervision for Document-Level Relation Extraction. EMNLP (1) (2021)
Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. CoRR (2020)
Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Marzyeh Ghassemi, Michael C. Hughes, Tristan Naumann
MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III. CHIL (2020)
Shems Saleh, William Boag, Lauren Erdman, Tristan Naumann
Clinical Collabsheets: 53 Questions to Guide a Clinical Collaboration. MLHC (2020)
Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Tristan Naumann, Brett K. Beaulieu-Jones, Adrian V. Dalca
ML4H Abstract Track 2019. CoRR (2020)
Emily Alsentzer, John R. Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, Matthew B. A. McDermott
Publicly Available Clinical BERT Embeddings. CoRR (2019)
Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Michael C. Hughes, Tristan Naumann, Marzyeh Ghassemi
MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III. CoRR (2019)
Aparna Balagopalan, Jekaterina Novikova, Matthew B. A. McDermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi
Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. ML4H@NeurIPS (2019)
Aparna Balagopalan, Jekaterina Novikova, Matthew B. A. McDermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi
Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. CoRR (2019)
Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. MLHC (2019)
Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. CoRR (2019)
Adrian V. Dalca, Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Corey Chivers, Andrew Beam, Tristan Naumann, Brett K. Beaulieu-Jones
Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different? ML4H@NeurIPS (2019)
Zexian Zeng, Yu Deng, Xiaoyu Li, Tristan Naumann, Yuan Luo
Natural Language Processing for EHR-Based Computational Phenotyping. IEEE ACM Trans. Comput. Biol. Bioinform. 16 (1) (2019)
Matthew B. A. McDermott, Tom Yan, Tristan Naumann, Nathan Hunt, Harini Suresh, Peter Szolovits, Marzyeh Ghassemi
Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs. AAAI (2018)
Natalia Antropova, Andrew L. Beam, Brett K. Beaulieu-Jones, Irene Chen, Corey Chivers, Adrian V. Dalca, Samuel G. Finlayson, Madalina Fiterau, Jason Alan Fries, Marzyeh Ghassemi, Mike Hughes, Bruno Jedynak, Jasvinder S. Kandola, Matthew B. A. McDermott, Tristan Naumann, Peter Schulam, Farah Shamout, Alexandre Yahi
Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. CoRR (2018)
Zexian Zeng, Yu Deng, Xiaoyu Li, Tristan Naumann, Yuan Luo
Natural Language Processing for EHR-Based Computational Phenotyping. CoRR (2018)
Dina Levy-Lambert, Jen J. Gong, Tristan Naumann, Tom J. Pollard, John V. Guttag
Visualizing Patient Timelines in the Intensive Care Unit. CoRR (2018)
Alistair E. W. Johnson, Tom J. Pollard, Tristan Naumann
Generalizability of predictive models for intensive care unit patients. CoRR (2018)
Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L. Beam, Rajesh Ranganath
Opportunities in Machine Learning for Healthcare. CoRR (2018)
Bret Nestor, Matthew B. A. McDermott, Geeticka Chauhan, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation. CoRR (2018)
Willie Boag, Elena Sergeeva, Saurabh Kulshreshtha, Peter Szolovits, Anna Rumshisky, Tristan Naumann
CliNER 2.0: Accessible and Accurate Clinical Concept Extraction. CoRR (2018)
Willie Boag, Tristan Naumann, Peter Szolovits
Towards the Creation of a Large Corpus of Synthetically-Identified Clinical Notes. CoRR (2018)
Jen J. Gong, Tristan Naumann, Peter Szolovits, John V. Guttag
Predicting Clinical Outcomes Across Changing Electronic Health Record Systems. KDD (2017)
Marzyeh Ghassemi, Marco A. F. Pimentel, Tristan Naumann, Thomas Brennan, David A. Clifton, Peter Szolovits, Mengling Feng
A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data. AAAI (2015)
Tristan Naumann, Ikaro Silva
Scaling the PhysioNet WFDB Toolbox for MATLAB and Octave. CinC (2014)
Marzyeh Ghassemi, Tristan Naumann, Finale Doshi-Velez, Nicole Brimmer, Rohit Joshi, Anna Rumshisky, Peter Szolovits
Unfolding physiological state: mortality modelling in intensive care units. KDD (2014)
Tristan Naumann, Marzyeh Ghassemi, Andreea Bodnari, Rohit Joshi
Probabilistically Populated Medical Record Templates: Reducing Clinical Documentation Time Using Patient Cooperation. AMIA (2013)

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Publication Activity (10 Years)

Top Topics

Top Venues

Tristan Naumann