Tristan Naumann
Microsoft (United States)(US)Microsoft Research (United Kingdom)(GB)
Publications by Year
Research Areas
Topic Modeling, Machine Learning in Healthcare, Biomedical Text Mining and Ontologies, Natural Language Processing Techniques, Artificial Intelligence in Healthcare and Education
Most-Cited Works
- → Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing(2021)1,897 cited
- → Publicly Available Clinical(2019)1,529 cited
- → Publicly Available Clinical BERT Embeddings(2019)720 cited
- → A whole-slide foundation model for digital pathology from real-world data(2024)520 cited
- → The role of machine learning in clinical research: transforming the future of evidence generation(2021)271 cited
- → A Review of Challenges and Opportunities in Machine Learning for Health(2018)253 cited
- → LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day(2023)222 cited
- → Natural Language Processing for EHR-Based Computational Phenotyping(2018)209 cited
- → Unfolding physiological state(2014)206 cited
- → Making the Most of Text Semantics to Improve Biomedical Vision–Language Processing(2022)206 cited