Hua Xu, PhD
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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
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Biomedical Informatics & Data Science
100 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
Contact Info
Biomedical Informatics & Data Science
100 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
Contact Info
Biomedical Informatics & Data Science
100 College St
New Haven, Connecticut 06510
United States
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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
Biography
Dr. Hua Xu is a well-known researcher in clinical natural language processing (NLP). He has developed novel algorithms for important clinical NLP tasks such as entity recognition and relation extraction, which have been top ranked in over a dozen of international biomedical NLP challenges. His lab has developed CLAMP, a comprehensive clinical NLP toolkit that has been successfully commercialized and used by hundreds of healthcare organizations. Moreover, he has led multiple national/international initiatives (e.g., Chair of the NLP working group at Observational Health Data Sciences and Informatics - OHDSI program) to apply developed NLP technologies to diverse clinical and translational studies, thus greatly accelerating clinical evidence generation using electronic health records data. Recently, he also utilizes NLP to harmonize metadata of biomedical digital objects (e.g., indexing millions of biomedical datasets to make them findable), with the goal to promote FAIR principles in biomedicine. Currently Dr. Xu's lab is actively working on developing large language models (LLMs) for diverse biomedical applications. See more information about Dr. Xu's lab here.
Appointments
Biomedical Informatics & Data Science
ProfessorPrimary
Other Departments & Organizations
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
Kalpana Raja, PhD, MRSB, CSci
Rohan Khera, MD, MS
Harlan Krumholz, MD, SM
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, He H, 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 ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsLanguage modelNatural language processing applicationsBiomedical natural language processingMedical question answeringLanguage processing applicationsNatural language processingGrowth of biomedical literatureMissing informationFew-shotQuestion AnsweringZero-ShotKnowledge curationLanguage processingProcessing applicationsBioNLPBART modelPerformance gapBiomedical literatureGeneral domainTaskBenchmarksBERTInformationPerformanceLLMMedical 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, He H, Shung D, 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 ResearchCitationsAltmetricConceptsText analysis tasksAnalysis tasksLanguage modelDomain-specific knowledgeZero-ShotHuman evaluationSupervised settingTask-specific instructionsClinical data sourcesSpecialized medical knowledgeChatGPTText analysisPretrainingTaskData sourcesMedical applicationsMedical knowledgeEnhanced performanceTextPerformanceImproving 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 ResearchCitationsConceptsClinical NER tasksNER taskTask-specific promptsEntity recognitionLanguage modelTraining samplesState-of-the-art modelsFew-shot learningState-of-the-artMinimal training dataTask-specific knowledgeF1-socreAnnotated samplesConcept extractionModel performanceAnnotated datasetsTraining dataF1 scoreTask descriptionFormat specificationsComplex clinical dataOptimal performanceTaskEvaluation schemaGPT modelBiomedRAG: 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 ResearchCitationsAltmetricMeSH Keywords and Concepts
2025
TopicForest: embedding-driven hierarchical clustering and labeling for biomedical literature
Chang C, Ondov B, Choi B, Peng X, He H, Xu H. TopicForest: embedding-driven hierarchical clustering and labeling for biomedical literature. Journal Of Biomedical Informatics 2025, 172: 104958. PMID: 41242669, DOI: 10.1016/j.jbi.2025.104958.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsAdjusted Mutual InformationBiomedical abstractsBiomedical literatureExpansion of biomedical literatureHierarchical topic modelHierarchical clusteringHierarchical clustering techniqueTopic hierarchyLabeling diversityTopic discoveryTopic summarizationClustering qualityClustering performanceManifold learningEmbedding modelTopic modelsLabel qualityLabeling frameworkSemantic spaceClustering techniqueMulti-scale explorationMutual informationCoherent labelingClustering methodDimension reductionExtracting language information from clinical notes using large language models
Qian L, Hong N, Zhou Y, Xie Q, Weng R, Chairuengjitjaras P, Du X, Lian J, Marshall G, Blackley S, Novoa-Laurentiev J, Quiroz Y, Kim T, Adams N, Dossett M, Zhou L, Xu H. Extracting language information from clinical notes using large language models. International Journal Of Medical Informatics 2025, 205: 106116. PMID: 40992205, PMCID: PMC12490899, DOI: 10.1016/j.ijmedinf.2025.106116.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsLanguage informationLanguage modelElectronic health recordsField of electronic health recordsYale-New Haven HospitalNER frameworkZero-ShotEntity recognitionInformation extractionMIMIC datasetF1 scoreClinical narrativesPatient-provider communicationClinical notesPatient-centered careMIMIC-IIIEquitable healthcare deliveryService allocationSuperior performanceCross-site validationAutomated extractionOpen-source modelHealth recordsBERTPatients' language proficiencyScientific Writing in the Era of Large Language Models: A Computational Analysis of AI- Versus Human-Created Content
Khera R, Pedroso A, Keloth V, Xu H, Silva G, Schwamm L. Scientific Writing in the Era of Large Language Models: A Computational Analysis of AI- Versus Human-Created Content. Stroke 2025, 56: 3078-3083. PMID: 40814778, DOI: 10.1161/strokeaha.125.051913.Peer-Reviewed Original ResearchAltmetricMeSH Keywords and ConceptsConceptsLanguage modelArtificial intelligenceAI-generatedLinguistic featuresDetection toolsAI-generated contentHuman-written textLanguage perplexityHuman expertsPerformance of expertsLinguistic differencesScientific textsGrade levelWord countEssayLanguageScientific communicationScientific writingComputer synthesisHigher grade levelsTextScientific contentReadability scoresPerplexityFlesch-KincaidAccuracy of Large Language Models in Generating Rare Disease Differential Diagnosis Using Key Clinical Features.
Shyr C, Tinker R, Harris P, Cheng A, Byram K, Bastarache L, Peterson J, Hamid R, Xu H, Cassini T. Accuracy of Large Language Models in Generating Rare Disease Differential Diagnosis Using Key Clinical Features. Studies In Health Technology And Informatics 2025, 329: 1054-1058. PMID: 40776018, DOI: 10.3233/shti251000.Peer-Reviewed Original ResearchCitationsChanges in Cardiovascular Risk Factors and Health Care Expenditures Among Patients Prescribed Semaglutide
Lu Y, Liu Y, Totojani T, Kim C, Khera R, Xu H, Brush J, Krumholz H, Abaluck J. Changes in Cardiovascular Risk Factors and Health Care Expenditures Among Patients Prescribed Semaglutide. JAMA Network Open 2025, 8: e2526013. PMID: 40779264, PMCID: PMC12334959, DOI: 10.1001/jamanetworkopen.2025.26013.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsHealth care expendituresCardiovascular risk factorsCare expendituresCohort studyRisk factorsYale New Haven Health SystemCohort study of adultsType 2 diabetes statusLong-term impactStudy of adultsHealth systemRetrospective cohort studyBlood pressureHemoglobin A1c reductionMain OutcomesTotal cholesterolSentara HealthcareInpatient staySecondary outcomesGlucagon-like peptide-1 receptor agonistsPrimary outcomeHealthPeptide-1 receptor agonistsAssociated with clinical outcomesAssociated with reductionsLarge Language Models for Rare Disease Diagnosis at the Undiagnosed Diseases Network
Shyr C, Cassini T, Tinker R, Byram K, Embí P, Bastarache L, Peterson J, Xu H, Hamid R. Large Language Models for Rare Disease Diagnosis at the Undiagnosed Diseases Network. JAMA Network Open 2025, 8: e2528538. PMID: 40844783, PMCID: PMC12374213, DOI: 10.1001/jamanetworkopen.2025.28538.Peer-Reviewed Original ResearchCitationsAltmetric
News
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News
- September 16, 2025Source: NIH
Yale Team Recognized in NIH $1 Million Data Sharing Challenge
- July 01, 2025
Hua Xu, PhD, Receives NIH Supplement to Advance Mental Health Research
- April 25, 2025
Yale BIDS Enhances Research with Comprehensive Data and Service Through YBIC
- March 18, 2025
Connecticut Academy of Science and Engineering Elects 12 From YSM
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Biomedical Informatics & Data Science
100 College St
New Haven, Connecticut 06510
United States
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