Tristan Naumann
Orcid: 0000-0003-2150-1747Affiliations:
- Microsoft Research, Redmond, WA, USA
According to our database1,
Tristan Naumann
authored at least 51 papers
between 2013 and 2024.
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Bibliography
2024
Training Small Multimodal Models to Bridge Biomedical Competency Gap: A Case Study in Radiology Imaging.
CoRR, 2024
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium.
CoRR, 2024
CoRR, 2024
2023
Patterns, April, 2023
Toward structuring real-world data: Deep learning for extracting oncology information from clinical text with patient-level supervision.
Patterns, April, 2023
TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models.
CoRR, 2023
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology.
CoRR, 2023
Distilling Large Language Models for Biomedical Knowledge Extraction: A Case Study on Adverse Drug Events.
CoRR, 2023
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day.
CoRR, 2023
An Investigation into the Effects of Pre-training Data Distributions for Pathology Report Classification.
CoRR, 2023
CoRR, 2023
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology.
Proceedings of the Machine Learning for Healthcare Conference, 2023
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023
Proceedings of the 5th Clinical Natural Language Processing Workshop, 2023
2022
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing.
ACM Trans. Comput. Heal., 2022
A collection of invited non-archival papers for the Conference on Health, Inference, and Learning (CHIL) 2022.
CoRR, 2022
Towards Structuring Real-World Data at Scale: Deep Learning for Extracting Key Oncology Information from Clinical Text with Patient-Level Supervision.
CoRR, 2022
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022
Proceedings of the Computer Vision - ECCV 2022, 2022
Proceedings of the Conference on Health, Inference, and Learning, 2022
2021
Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
2020
Proceedings of the Machine Learning for Healthcare Conference, 2020
MIMIC-Extract: a data extraction, preprocessing, and representation pipeline for MIMIC-III.
Proceedings of the ACM CHIL '20: ACM Conference on Health, 2020
2019
IEEE ACM Trans. Comput. Biol. Bioinform., 2019
Machine Learning for Health ( ML4H ) 2019 : What Makes Machine Learning in Medicine Different?
Proceedings of the Machine Learning for Health Workshop, 2019
Proceedings of the Machine Learning for Health Workshop, 2019
Feature Robustness in Non-stationary Health Records: Caveats to Deployable Model Performance in Common Clinical Machine Learning Tasks.
Proceedings of the Machine Learning for Healthcare Conference, 2019
2018
Rethinking clinical prediction: Why machine learning must consider year of care and feature aggregation.
CoRR, 2018
CoRR, 2018
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018
2017
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017
2015
A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
2014
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014
Proceedings of the Computing in Cardiology, CinC 2014, 2014
2013
Probabilistically Populated Medical Record Templates: Reducing Clinical Documentation Time Using Patient Cooperation.
Proceedings of the AMIA 2013, 2013