Tristan Naumann

88 papers A* 10Misc 1Journal 54Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Exploring the Future of AI in Clinical Collaboration: A Study on Tumor Board Case Preparation. CHI Jiachen Li, Amanda K. Hall, Ruican Rachel Zhong, Selin S. Everett, Alyssa Unell, Hanwen Xu, Matthias Blondeel, Jonathan Carlson, Katie Claveau, Thulasee Jose, Tristan Naumann, David C. Rhew, Naiteek Sangani, Frank Tuan, James Weinstein, Varun Mishra, Elizabeth D. Mynatt, T. Scott Saponas, Hao Qiu, Leonardo Schettini, Joseph Samuel Preston, Aiden Gu, Naoto Usuyama, Zelalem Gero, Cliff Wong, Noel Christopher Codella, Hoifung Poon, Shrey Jain, Matthew P. Lungren, Eric Horvitz
2026	J	`jnl`	Learning Sparse Visual Representations via Spatial-Semantic Factorization. CoRR Theodore Zhengde Zhao, Sid Kiblawi, Jianwei Yang, Naoto Usuyama, Reuben Tan, Noel C. F. Codella, Tristan Naumann, Hoifung Poon, Mu Wei
2026	J	`jnl`	Scaling medical imaging report generation with multimodal reinforcement learning. CoRR Qianchu Liu, Sheng Zhang, Guanghui Qin, Yu Gu, Ying Jin, Sam Preston, Yanbo Xu, Sid Kiblawi, Wen-Wai Yim, Timothy Ossowski, Tristan Naumann, Mu Wei, Hoifung Poon
2025	J	`jnl`	Be My Eyes: Extending Large Language Models to New Modalities Through Multi-Agent Collaboration. CoRR James Y. Huang, Sheng Zhang, Qianchu Liu, Guanghui Qin, Tinghui Zhu, Tristan Naumann, Muhao Chen, Hoifung Poon
2025	J	`jnl`	BioClinical ModernBERT: A State-of-the-Art Long-Context Encoder for Biomedical and Clinical NLP. CoRR Thomas Sounack, Joshua Davis, Brigitte N. Durieux, Antoine Chaffin, Tom J. Pollard, Eric Lehman, Alistair E. W. Johnson, Matthew B. A. McDermott, Tristan Naumann, Charlotta Lindvall
2025	J	`jnl`	Exploring Scaling Laws for EHR Foundation Models. CoRR Sheng Zhang, Qin Liu, Naoto Usuyama, Cliff Wong, Tristan Naumann, Hoifung Poon
2025	J	`jnl`	Generative Medical Event Models Improve with Scale. CoRR Shane Waxler, Paul Blazek, Davis White, Daniel Sneider, Kevin Chung, Mani Nagarathnam, Patrick Williams, Hank Voeller, Karen Wong, Matthew Swanhorst, Sheng Zhang, Naoto Usuyama, Cliff Wong, Tristan Naumann, Hoifung Poon, Andrew Loza, Daniella Meeker, Seth Hain, Rahul Shah
2025	J	`jnl`	Introduction to the Special Issue on Large Language Models, Conversational Systems, and Generative AI in Health - Part 1. ACM Trans. Comput. Heal. Jiayu Zhou, Manas Gaur, Amir M. Rahmani, Sharath Chandra Guntuku, Xiaofan Fred Jiang, Tristan Naumann
2025	J	`jnl`	Med-RLVR: Emerging Medical Reasoning from a 3B base model via reinforcement Learning. CoRR Sheng Zhang, Qianchu Liu, Guanghui Qin, Tristan Naumann, Hoifung Poon
2025	J	`jnl`	OctoMed: Data Recipes for State-of-the-Art Multimodal Medical Reasoning. CoRR Timothy Ossowski, Sheng Zhang, Qianchu Liu, Guanghui Qin, Reuben Tan, Tristan Naumann, Junjie Hu, Hoifung Poon
2025	J	`jnl`	Towards responsible artificial intelligence in healthcare - getting real about real-world data and evidence. J. Am. Medical Informatics Assoc. Eileen Koski, Amar K. Das, Pei-Yun Sabrina Hsueh, Anthony Solomonides, Amanda L. Joseph, Gyana Srivastava, Carl Erwin Johnson, Joseph L. Kannry, Bilikis Oladimeji, Amy Price, Steven E. Labkoff, Gnana Bharathy, Baihan Lin, Douglas B. Fridsma, Lee A. Fleisher, Mónica López-González, Reva Singh, Mark G. Weiner, Robert Stolper, Russell Baris, Suzanne Sincavage, Tristan Naumann, Tayler Williams, Tien Thi Thuy Bui, Yuri Quintana
2025	J	`jnl`	Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale. CoRR Cliff Wong, Sam Preston, Qianchu Liu, Zelalem Gero, Jass Bagga, Sheng Zhang, Shrey Jain, Theodore Zhao, Yu Gu, Yanbo Xu, Sid Kiblawi, Roshanthi Weerasinghe, Rom S. Leidner, Kristina Young, Brian Piening, Carlo Bifulco, Tristan Naumann, Mu Wei, Hoifung Poon
2025	J	`jnl`	X-Reasoner: Towards Generalizable Reasoning Across Modalities and Domains. CoRR Qianchu Liu, Sheng Zhang, Guanghui Qin, Timothy Ossowski, Yu Gu, Ying Jin, Sid Kiblawi, Sam Preston, Mu Wei, Paul Vozila, Tristan Naumann, Hoifung Poon
2024	J	`jnl`	Attribute Structuring Improves LLM-Based Evaluation of Clinical Text Summaries. CoRR Zelalem Gero, Chandan Singh, Yiqing Xie, Sheng Zhang, Tristan Naumann, Jianfeng Gao, Hoifung Poon
2024	—	`conf`	Beyond Clinical Trials: Using Real World Evidence to Investigate Heterogeneous, Time-Varying Treatment Effects. MLHC 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
2024	J	`jnl`	BiomedParse: a biomedical foundation model for image parsing of everything everywhere all at once. CoRR 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
2024	A*	`conf`	Diagnosing Transformers: Illuminating Feature Spaces for Clinical Decision-Making. ICLR Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu
2024	—	`conf`	DocLens: Multi-aspect Fine-grained Medical Text Evaluation. ACL (1) Yiqing Xie, Sheng Zhang, Hao Cheng, Pengfei Liu, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon, Carolyn P. Rosé
2024	—	`ed.`	Proceedings of the 6th Clinical Natural Language Processing Workshop, ClinicalNLP@NAACL 2024, Mexico City, Mexico, June 21, 2024 ClinicalNLP@NAACL Tristan Naumann, Asma Ben Abacha, Steven Bethard, Kirk Roberts, Danielle S. Bitterman
2024	J	`jnl`	Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR 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
2024	J	`jnl`	Toward a responsible future: recommendations for AI-enabled clinical decision support. J. Am. Medical Informatics Assoc. Steven E. Labkoff, Bilikis Oladimeji, Joseph L. Kannry, Anthony Solomonides, Russell Leftwich, Eileen Koski, Amanda L. Joseph, Mónica López-González, Lee A. Fleisher, Kimberly Nolen, Sayon Dutta, Deborah R. Levy, Amy Price, Paul J. Barr, Jonathan D. Hron, Baihan Lin, Gyana Srivastava, Nuria Pastor, Unai Sánchez Luque, Tien Thi Thuy Bui, Reva Singh, Tayler Williams, Mark G. Weiner, Tristan Naumann, Dean F. Sittig, Gretchen Purcell Jackson, Yuri Quintana
2024	J	`jnl`	Training Small Multimodal Models to Bridge Biomedical Competency Gap: A Case Study in Radiology Imaging. CoRR 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
2023	A*	`ed.`	Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023. NeurIPS Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, Sergey Levine
2023	J	`jnl`	An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification. CoRR Aliyah R. Hsu, Yeshwanth Cherapanamjeri, Briton Park, Tristan Naumann, Anobel Y. Odisho, Bin Yu
2023	J	`jnl`	Compositional Zero-Shot Domain Transfer with Text-to-Text Models. CoRR 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
2023	J	`jnl`	Compositional Zero-Shot Domain Transfer with Text-to-Text Models. Trans. Assoc. Comput. Linguistics 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
2023	—	`conf`	Continual Contrastive Finetuning Improves Low-Resource Relation Extraction. ACL (1) Wenxuan Zhou, Sheng Zhang, Tristan Naumann, Muhao Chen, Hoifung Poon
2023	J	`jnl`	Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events. CoRR Yu Gu, Sheng Zhang, Naoto Usuyama, Yonas Woldesenbet, Cliff Wong, Praneeth Sanapathi, Mu Wei, Naveen Valluri, Erika Strandberg, Tristan Naumann, Hoifung Poon
2023	J	`jnl`	Enhancing Medical Text Evaluation with GPT-4. CoRR Yiqing Xie, Sheng Zhang, Hao Cheng, Zelalem Gero, Cliff Wong, Tristan Naumann, Hoifung Poon
2023	J	`jnl`	Fine-tuning large neural language models for biomedical natural language processing. Patterns Robert Tinn, Hao Cheng, Yu Gu, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
2023	A*	`conf`	LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. NeurIPS Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao
2023	J	`jnl`	LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day. CoRR Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao
2023	J	`jnl`	Large-Scale Domain-Specific Pretraining for Biomedical Vision-Language Processing. CoRR 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
2023	A*	`conf`	Precision Health in the Age of Large Language Models. KDD Hoifung Poon, Tristan Naumann, Sheng Zhang, Javier González Hernández
2023	—	`ed.`	Proceedings of the 5th Clinical Natural Language Processing Workshop, ClinicalNLP@ACL 2023, Toronto, Canada, July 14, 2023. ClinicalNLP@ACL Tristan Naumann, Asma Ben Abacha, Steven Bethard, Kirk Roberts, Anna Rumshisky
2023	—	`conf`	Prompt Discriminative Language Models for Domain Adaptation. ClinicalNLP@ACL Keming Lu, Peter Potash, Xihui Lin, Yuwen Sun, Zihan Qian, Zheng Yuan, Tristan Naumann, Tianxi Cai, Junwei Lu
2023	—	`conf`	Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology. MLHC Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon
2023	J	`jnl`	Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology. CoRR Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon
2023	J	`jnl`	Self-Verification Improves Few-Shot Clinical Information Extraction. CoRR Zelalem Gero, Chandan Singh, Hao Cheng, Tristan Naumann, Michel Galley, Jianfeng Gao, Hoifung Poon
2023	J	`jnl`	TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models. CoRR 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
2023	J	`jnl`	Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision. Patterns 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
2023	—	`conf`	What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization. ACL (1) Griffin Adams, Bichlien Nguyen, Jake Smith, Yingce Xia, Shufang Xie, Anna Ostropolets, Budhaditya Deb, Yuan-Jyue Chen, Tristan Naumann, Noémie Elhadad
2023	J	`jnl`	What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization. CoRR Griffin Adams, Bichlien H. Nguyen, Jake Smith, Yingce Xia, Shufang Xie, Anna Ostropolets, Budhaditya Deb, Yuan-Jyue Chen, Tristan Naumann, Noémie Elhadad
2022	J	`jnl`	A collection of invited non-archival papers for the Conference on Health, Inference, and Learning (CHIL) 2022. CoRR Gerardo Flores, George H. Chen, Tom J. Pollard, Joyce C. Ho, Tristan Naumann
2022	—	`conf`	Conference on Health, Inference, and Learning (CHIL) 2022. CHIL Gerardo Flores, George H. Chen, Tom J. Pollard, Ayah Zirikly, Michael C. Hughes, Tasmie Sarker, Joyce C. Ho, Tristan Naumann
2022	—	`ed.`	Conference on Health, Inference, and Learning, CHIL 2022, 7-8 April 2022, Virtual Event. CHIL Gerardo Flores, George H. Chen, Tom J. Pollard, Joyce C. Ho, Tristan Naumann
2022	J	`jnl`	Continual Contrastive Finetuning Improves Low-Resource Relation Extraction. CoRR Wenxuan Zhou, Sheng Zhang, Tristan Naumann, Muhao Chen, Hoifung Poon
2022	J	`jnl`	Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. ACM Trans. Comput. Heal. Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
2022	—	`conf`	Knowledge-Rich Self-Supervision for Biomedical Entity Linking. EMNLP (Findings) Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
2022	—	`conf`	Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. ECCV (36) 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
2022	J	`jnl`	Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. CoRR 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
2022	J	`jnl`	Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision. CoRR 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
2021	—	`ed.`	ACM CHIL '21: ACM Conference on Health, Inference, and Learning, Virtual Event, USA, April 8-9, 2021 CHIL Marzyeh Ghassemi, Tristan Naumann, Emma Pierson
2021	A*	`conf`	Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature. KDD 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
2021	J	`jnl`	Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature. CoRR 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
2021	J	`jnl`	Fine-Tuning Large Neural Language Models for Biomedical Natural Language Processing. CoRR Robert Tinn, Hao Cheng, Yu Gu, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
2021	J	`jnl`	Knowledge-Rich Self-Supervised Entity Linking. CoRR Sheng Zhang, Hao Cheng, Shikhar Vashishth, Cliff Wong, Jinfeng Xiao, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
2021	—	`conf`	Modular Self-Supervision for Document-Level Relation Extraction. EMNLP (1) Sheng Zhang, Cliff Wong, Naoto Usuyama, Sarthak Jain, Tristan Naumann, Hoifung Poon
2021	J	`jnl`	Modular Self-Supervision for Document-Level Relation Extraction. CoRR Sheng Zhang, Cliff Wong, Naoto Usuyama, Sarthak Jain, Tristan Naumann, Hoifung Poon
2020	—	`conf`	Clinical Collabsheets: 53 Questions to Guide a Clinical Collaboration. MLHC Shems Saleh, William Boag, Lauren Erdman, Tristan Naumann
2020	J	`jnl`	Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing. CoRR Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, Hoifung Poon
2020	—	`conf`	MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III. CHIL Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Marzyeh Ghassemi, Michael C. Hughes, Tristan Naumann
2020	J	`jnl`	ML4H Abstract Track 2019. CoRR Matthew B. A. McDermott, Emily Alsentzer, Samuel G. Finlayson, Michael Oberst, Fabian Falck, Tristan Naumann, Brett K. Beaulieu-Jones, Adrian V. Dalca
2020	—	`ed.`	Proceedings of the 3rd Clinical Natural Language Processing Workshop, ClinicalNLP@EMNLP 2020, Online, November 19, 2020 ClinicalNLP@EMNLP Anna Rumshisky, Kirk Roberts, Steven Bethard, Tristan Naumann
2019	—	`conf`	Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. ML4H@NeurIPS Aparna Balagopalan, Jekaterina Novikova, Matthew B. A. McDermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi
2019	J	`jnl`	Cross-Language Aphasia Detection using Optimal Transport Domain Adaptation. CoRR Aparna Balagopalan, Jekaterina Novikova, Matthew B. A. McDermott, Bret Nestor, Tristan Naumann, Marzyeh Ghassemi
2019	—	`conf`	Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. MLHC Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
2019	J	`jnl`	Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks. CoRR Bret Nestor, Matthew B. A. McDermott, Willie Boag, Gabriela Berner, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
2019	J	`jnl`	MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III. CoRR Shirly Wang, Matthew B. A. McDermott, Geeticka Chauhan, Michael C. Hughes, Tristan Naumann, Marzyeh Ghassemi
2019	—	`conf`	Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different? ML4H@NeurIPS 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
2019	J	`jnl`	Natural Language Processing for EHR-Based Computational Phenotyping. IEEE ACM Trans. Comput. Biol. Bioinform. Zexian Zeng, Yu Deng, Xiaoyu Li, Tristan Naumann, Yuan Luo
2019	J	`jnl`	Publicly Available Clinical BERT Embeddings. CoRR Emily Alsentzer, John R. Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, Matthew B. A. McDermott
2018	J	`jnl`	CliNER 2.0: Accessible and Accurate Clinical Concept Extraction. CoRR Willie Boag, Elena Sergeeva, Saurabh Kulshreshtha, Peter Szolovits, Anna Rumshisky, Tristan Naumann
2018	J	`jnl`	Generalizability of predictive models for intensive care unit patients. CoRR Alistair E. W. Johnson, Tom J. Pollard, Tristan Naumann
2018	—	`—`	Leveraging text representations for clinical predictive tasks. Tristan Naumann
2018	J	`jnl`	Machine Learning for Health (ML4H) Workshop at NeurIPS 2018. CoRR 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
2018	J	`jnl`	Natural Language Processing for EHR-Based Computational Phenotyping. CoRR Zexian Zeng, Yu Deng, Xiaoyu Li, Tristan Naumann, Yuan Luo
2018	J	`jnl`	Opportunities in Machine Learning for Healthcare. CoRR Marzyeh Ghassemi, Tristan Naumann, Peter Schulam, Andrew L. Beam, Rajesh Ranganath
2018	J	`jnl`	Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation. CoRR Bret Nestor, Matthew B. A. McDermott, Geeticka Chauhan, Tristan Naumann, Michael C. Hughes, Anna Goldenberg, Marzyeh Ghassemi
2018	A*	`conf`	Semi-Supervised Biomedical Translation With Cycle Wasserstein Regression GANs. AAAI Matthew B. A. McDermott, Tom Yan, Tristan Naumann, Nathan Hunt, Harini Suresh, Peter Szolovits, Marzyeh Ghassemi
2018	J	`jnl`	Towards the Creation of a Large Corpus of Synthetically-Identified Clinical Notes. CoRR Willie Boag, Tristan Naumann, Peter Szolovits
2018	J	`jnl`	Visualizing Patient Timelines in the Intensive Care Unit. CoRR Dina Levy-Lambert, Jen J. Gong, Tristan Naumann, Tom J. Pollard, John V. Guttag
2017	A*	`conf`	Predicting Clinical Outcomes Across Changing Electronic Health Record Systems. KDD Jen J. Gong, Tristan Naumann, Peter Szolovits, John V. Guttag
2016	—	`ed.`	Proceedings of the Clinical Natural Language Processing Workshop, ClinicalNLP@COLING 2016, Osaka, Japan, December 11, 2016 ClinicalNLP@COLING 2016 Anna Rumshisky, Kirk Roberts, Steven Bethard, Tristan Naumann
2015	A*	`conf`	A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data. AAAI Marzyeh Ghassemi, Marco A. F. Pimentel, Tristan Naumann, Thomas Brennan, David A. Clifton, Peter Szolovits, Mengling Feng
2014	—	`conf`	Scaling the PhysioNet WFDB Toolbox for MATLAB and Octave. CinC Tristan Naumann, Ikaro Silva
2014	A*	`conf`	Unfolding physiological state: mortality modelling in intensive care units. KDD Marzyeh Ghassemi, Tristan Naumann, Finale Doshi-Velez, Nicole Brimmer, Rohit Joshi, Anna Rumshisky, Peter Szolovits
2013	Misc	`conf`	Probabilistically Populated Medical Record Templates: Reducing Clinical Documentation Time Using Patient Cooperation. AMIA Tristan Naumann, Marzyeh Ghassemi, Andreea Bodnari, Rohit Joshi