College of Medicine
Jie Xu Lab
Led by Jie Xu · Health Outcomes and Biomedical Informatics
What we study
The Xu Lab develops AI and machine learning tools to analyze healthcare data like medical records and imaging. They focus on patient similarity, disease prediction, and privacy-preserving methods like federated learning.
What working here is like
- Computational
- No organisms (data only)
- Coding required
- Projects
- 4
Current projects
A Portfolio of Use Cases to Enable Privacy-Preserving AI with Federated Learning
Developing AI tools that protect patient privacy while analyzing medical data across institutions.
Deriving Real World Insights to Inform Trials for Pregnant Individuals Using Electronic Health Records and Machine Learning
Using medical records and AI to improve research for pregnant individuals.
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Advancing Renal Mass Diagnosis and Management through AI-Enhanced Decision Support Systems
Creating AI tools to help diagnose and manage kidney conditions.
Identifying pediatric asthma subtypes using novel privacy-preserving federated machine learning methods
Using AI to study different types of asthma in children while keeping data private.
Summaries are written by AI in plain language from public symposium abstracts and may be imperfect.
How to reach out
Jie Xu hasn't set up this page yet. Their UF Scholars profile lists their publications.