Hua Xu, PhD
Cards
Appointments
Additional Titles
Vice Chair for Research and Development, Department of Biomedical Informatics and Data Science
Associate Dean for Biomedical Informatics, Yale School of Medicine
Director, CBB MS Program , Biomedical Informatics & Data Science
Professor, Computer Science
Contact Info
Biomedical Informatics & Data Science
101 College St
New Haven, Connecticut 06510
United States
Appointments
Additional Titles
Vice Chair for Research and Development, Department of Biomedical Informatics and Data Science
Associate Dean for Biomedical Informatics, Yale School of Medicine
Director, CBB MS Program , Biomedical Informatics & Data Science
Professor, Computer Science
Contact Info
Biomedical Informatics & Data Science
101 College St
New Haven, Connecticut 06510
United States
Appointments
Additional Titles
Vice Chair for Research and Development, Department of Biomedical Informatics and Data Science
Associate Dean for Biomedical Informatics, Yale School of Medicine
Director, CBB MS Program , Biomedical Informatics & Data Science
Professor, Computer Science
Contact Info
Biomedical Informatics & Data Science
101 College St
New Haven, Connecticut 06510
United States
About
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Titles
Robert T. McCluskey Professor of Biomedical Informatics and Data Science
Vice Chair for Research and Development, Department of Biomedical Informatics and Data Science; Associate Dean for Biomedical Informatics, Yale School of Medicine; Director, CBB MS Program , Biomedical Informatics & Data Science; Professor, Computer Science
Biography
Dr. Hua Xu is Robert T. McCluskey Professor and Vice Chair for Research and Development, Department of Biomedical Informatics and Data Science at Yale School of Medicine (YSM). He also serves as Associate Dean for Biomedical Informatics at YSM. He received his Ph.D. in Biomedical Informatics from Columbia University. His primary research interests include biomedical natural language processing (NLP), large language models (LLMs), and AI agents, as well as their applications in clinical practice and biomedical research. His research is funded by multiple agencies (i.e., NLM, NCI, NIGMS, NIA, AHA, and CPRIT), and methods/tools developed in his lab have been widely used to support diverse biomedical applications. Dr. Xu is a fellow of both the American College of Medical Informatics (ACMI) and the International Academy of Health Sciences Informatics (IAHSI). See more information about Dr. Xu's lab here.
Appointments
Biomedical Informatics & Data Science
ProfessorPrimaryComputer Science
ProfessorSecondary
Other Departments & Organizations
- Biomedical Informatics & Data Science
- Clinical NLP Lab
- Computational Biology and Biomedical Informatics
- Computer Science
- Wu Tsai Institute
- Yale Biomedical Informatics & Computing
- Yale Combined Program in the Biological and Biomedical Sciences (BBS)
Education & Training
- PhD
- Columbia University, Biomedical Informatics
- MS
- New Jersey Institute of Technology, Computer Science
- BS
- Nanjing University, Biochemistry
Research
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Overview
Medical Research Interests
ORCID
0000-0002-5274-4672- View Lab Website
Clinical NLP Lab
Research at a Glance
Yale Co-Authors
Publications Timeline
Research Interests
Lucila Ohno-Machado, MD, MBA, PhD
Vipina K. Keloth, PhD
Qingyu Chen, PhD
Na Hong, PhD
Harlan Krumholz, MD, SM
Kalpana Raja, PhD, MRSB, CSci
Natural Language Processing
Publications
Featured Publications
Benchmarking large language models for biomedical natural language processing applications and recommendations
Chen Q, Hu Y, Peng X, Xie Q, Jin Q, Gilson A, Singer M, Ai X, Lai P, Wang Z, Keloth V, Raja K, Huang J, Lin F, Du J, Zhang R, Zheng W, Adelman R, Lu Z, Xu H. Benchmarking large language models for biomedical natural language processing applications and recommendations. Nature Communications 2025, 16: 3280. PMID: 40188094, PMCID: PMC11972378, DOI: 10.1038/s41467-025-56989-2.Peer-Reviewed Original ResearchCitationsAltmetricMedical foundation large language models for comprehensive text analysis and beyond
Xie Q, Chen Q, Chen A, Peng C, Hu Y, Lin F, Peng X, Huang J, Zhang J, Keloth V, Zhou X, Qian L, Ohno-Machado L, Wu Y, Xu H, Bian J. Medical foundation large language models for comprehensive text analysis and beyond. Npj Digital Medicine 2025, 8: 141. PMID: 40044845, PMCID: PMC11882967, DOI: 10.1038/s41746-025-01533-1.Peer-Reviewed Original ResearchCitationsImproving large language models for clinical named entity recognition via prompt engineering
Hu Y, Chen Q, Du J, Peng X, Keloth V, Zuo X, Zhou Y, Li Z, Jiang X, Lu Z, Roberts K, Xu H. Improving large language models for clinical named entity recognition via prompt engineering. Journal Of The American Medical Informatics Association 2024, 31: 1812-1820. PMID: 38281112, PMCID: PMC11339492, DOI: 10.1093/jamia/ocad259.Peer-Reviewed Original ResearchCitationsBiomedRAG: A retrieval augmented large language model for biomedicine
Li M, Kilicoglu H, Xu H, Zhang R. BiomedRAG: A retrieval augmented large language model for biomedicine. Journal Of Biomedical Informatics 2025, 162: 104769. PMID: 39814274, PMCID: PMC11837810, DOI: 10.1016/j.jbi.2024.104769.Peer-Reviewed Original ResearchCitationsAltmetric
2026
Discovering repurposable drugs for Alzheimer’s disease and related dementias: target trial emulation using decentralised real-world data
Wu Q, Li L, Lei Y, Zhou T, Tang H, Zhang B, Lu Y, Salvatore M, Zhang D, Tong J, Wang T, Chen S, Li H, Xu Z, Huang Y, Hu Y, Hong N, Zhou Y, Lin F, O’Brien K, Chen Y, Li R, Xu H, Wang F, Bian J, Wolk D, Chen Y. Discovering repurposable drugs for Alzheimer’s disease and related dementias: target trial emulation using decentralised real-world data. EBioMedicine 2026, 132: 106466. PMID: 42697072, PMCID: PMC13572180, DOI: 10.1016/j.ebiom.2026.106466.Peer-Reviewed Original ResearchAltmetricToward federated large language models in medicine: a parameter-efficient framework for privacy-preserving, multi-institutional adaptation
Li A, Chen Y, Long W, Yin Y, Hu Y, Kim H, Zhou W, Zhou Y, Peng H, Ren Y, Ai X, Qin Z, Hu M, Li X, Yu H, Tham Y, Ohno-Machado L, Xu H, Chen Q. Toward federated large language models in medicine: a parameter-efficient framework for privacy-preserving, multi-institutional adaptation. Npj Digital Medicine 2026 DOI: 10.1038/s41746-026-03064-9.Peer-Reviewed Original ResearchAltmetricDiagnostic accuracy of large language models for rare diseases: a systematic review and meta-analysis
Nguyen M, Yang C, Cassini T, Ma F, Hamid R, Bastarache L, Peterson J, Xu H, Li L, Ma S, Shyr C. Diagnostic accuracy of large language models for rare diseases: a systematic review and meta-analysis. Npj Digital Medicine 2026 DOI: 10.1038/s41746-026-03109-z.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsAltmetricCiteSure: retrieval-augmented large language models for faithful biomedical citation recommendation
Xie Q, Zhang J, Wang Y, Huang J, Lin F, Weng R, Chen Q, Xu H. CiteSure: retrieval-augmented large language models for faithful biomedical citation recommendation. Journal Of The American Medical Informatics Association 2026, ocag122. PMID: 42551844, DOI: 10.1093/jamia/ocag122.Peer-Reviewed Original ResearchPDA (Privacy-Preserving Distributed Algorithms) in action: ten principles for high-quality multi-site clinical evidence generation
Chen Y, Tong J, Lu Y, Duan R, Luo C, Suchard M, Ryan P, Williams A, Holmes J, Moore J, Xu H, Lu Y, Carroll R, Zeger S, Hripcsak G, Schuemie M. PDA (Privacy-Preserving Distributed Algorithms) in action: ten principles for high-quality multi-site clinical evidence generation. Journal Of The American Medical Informatics Association 2026, 33: 1636-1648. PMID: 42440280, PMCID: PMC13580733, DOI: 10.1093/jamia/ocag119.Peer-Reviewed Original ResearchCitationsMemorization in large language models in medicine prevalence characteristics and implications
Li A, Qian L, Du M, Yin Y, Hu Y, Sun Z, Fu Y, Kim H, Stutz E, Ai X, Xie Q, Zhu R, Huang J, Yang Y, Liu S, Tham Y, Ohno-Machado L, Cho H, Lu Z, Xu H, Chen Q. Memorization in large language models in medicine prevalence characteristics and implications. Nature Communications 2026, 17: 7729. PMID: 42315854, PMCID: PMC13434820, DOI: 10.1038/s41467-026-73779-6.Peer-Reviewed Original ResearchThis study systematically examined what large language models memorize when adapted for medicine, how frequently memorization occurs, how much content is retained, and how it may affect downstream medical applications.
News
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News
- September 10, 2026
Xu and Team Awarded NIH R01 Grant to Study GLP-1 Drugs and Mental Health
- September 09, 2026
Yale-Led Team Awarded $9.5M NIH Grant to Coordinate Artificial Intelligence and Technology Collaboratory (AITC) Program on Aging and AD/ADRD Research
- July 22, 2026
Jiang and Cheng Awarded Yale POINTS Grant for Low-Cost Long-Read Sequencing Platform
- April 29, 2026
BIDS Graduates First CB&B Master's Cohort
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Biomedical Informatics & Data Science
101 College St
New Haven, Connecticut 06510
United States