College of Medicine
Wu Lab
Led by Yonghui Wu · Health Outcomes and Biomedical Informatics
What we study
The Wu Lab uses AI and machine learning to analyze electronic health records and develop tools for medical discovery. Their work focuses on natural language processing, large language models, and computational drug discovery.
What working here is like
- Computational
- Coding required
- Projects
- 4
Current projects
Integrative Real-World Data and AI for Identifying Alzheimer’s Disease Progression Rate-based Sub-phenotypes and Associated Risk Factors
Using AI to analyze real-world data to understand Alzheimer’s disease progression.
ReCARDO: Using Real-World Data (RWD) to Derive Common Data Elements (CDEs) for Alzheimer’s Disease (AD) and AD-Related Dementias…
Developing data standards for Alzheimer’s disease research using real-world data.
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Improve adoption of clinical text in multi-site studies through transfer learning and natural language processing
Enhancing the use of clinical text in research through AI techniques.
Multimodal Multi-Medical Task Adaptive Guidance System (Multi-TAGs)
Builds an AI system that guides researchers through medical tasks using text, images and other types of data.
Summaries are written by AI in plain language from public symposium abstracts and may be imperfect.
How to reach out
Yonghui Wu hasn't set up this page yet. Their UF Scholars profile lists their publications.