Qingyu Chen, PhD
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Assistant Professor of Biomedical Informatics and Data Science
Biography
Dr. Qingyu Chen is an incoming tenure-track assistant professor at Biomedical Informatics & Data Science, School of Medicine at Yale. He is setting up his lab in 2024. Dr. Chen has led the major milestone in AI and data science in healthcare from data generation to method development and further to practical applications. His research focuses on Artificial Intelligence and data science for healthcare and biomedicine, including but limited to the following areas:
- Biomedical text mining and information retrieval
- Medical image analytics and multimodal analysis
- AI-assisted healthcare applications
- Biocuration
Hiring
I am setting up my lab and always look for postdoc fellows, PhD students, and interns. Check my work and feel free to reach out at qingyu.chen@yale.edu
Achievements for bean counters
~40 first-authored papers out of ~70 in total
Work has been in Nature, Nature Machine Intelligence, Nature Aging, NPJ digital medicine, Nucleic Acids Research, Ophthalmology, Bioinformatics, Journal of the American Medical Informatics Association, and many others
Main awards include AI Talent Scholar (Top 50 in AI in cross-disciplines) selected by Baidu Scholar, NIH Fellows Award for Research Excellence (two times), NIH Summer Research Mentor Award (four times), NLM Honor Award (two times), Excellence in Teaching Awards (two times), and Top-ranked performance in biomedical and clinical NLP challenges as the first author (three times)
Taught over 20 courses and mentored over 10 students
Reviewed ~180 manuscripts and handled ~40 manuscripts as the editor
Developed one of the first series of biomedical language models including BioWordVec, BioSentVec, BioConceptVec, Multi-task BlueBERT, and Bioformer and AI-assisted healthcare applications including LitCovid, LitSuggest, LitSense, DeepSeeNet, M3-RPD, and DeepLensNet that have been accessed by millions of biomedical researchers and healthcare professionals
For more information, please visit https://sites.google.com/view/qingyuchen/home.
Appointments
Biomedical Informatics & Data Science
Assistant ProfessorPrimaryOphthalmology
Associate Research ScientistSecondary
Other Departments & Organizations
Education & Training
- PhD
- University of Melbourne, Computer Science and Biomedical Informatics (Microsoft Innovation Award; Excellence in Teaching Award; Top-ranked performance in AI challenge tasks
- BS (Hon)
- The Royal Melbourne Institute of Technology, Computer Science (GPA ranked 1st; First-class Honor; Academic Excellence Award) (2013)
Research
Overview
~40 first-authored papers out of ~70 in total
Work has been in Nature, Nature Machine Intelligence, Nature Aging, NPJ digital medicine, Nucleic Acids Research, Ophthalmology, Bioinformatics, Journal of the American Medical Informatics Association, and many others
Main awards include AI Talent Scholar (Top 50 in AI in cross-disciplines) selected by Baidu Scholar, NIH Fellows Award for Research Excellence (two times), NIH Summer Research Mentor Award (four times), NLM Honor Award (two times), Excellence in Teaching Awards (two times), and Top-ranked performance in biomedical and clinical NLP challenges as the first author (three times)
Taught over 20 courses and mentored over 10 students
Reviewed ~180 manuscripts and handled ~40 manuscripts as the editor
Developed one of the first series of biomedical language models including BioWordVec, BioSentVec, BioConceptVec, Multi-task BlueBERT, and Bioformer and AI-assisted healthcare applications including LitCovid, LitSuggest, LitSense, DeepSeeNet, M3-RPD, and DeepLensNet that have been accessed by millions of biomedical researchers and healthcare professionals
For more information, please visit https://sites.google.com/view/qingyuchen/home.
Research at a Glance
Yale Co-Authors
Publications Timeline
Hua Xu, PhD
Ron Adelman, MD, MPH, MBA, FACS
Publications
2024
Outpatient reception via collaboration between nurses and a large language model: a randomized controlled trial
Wan P, Huang Z, Tang W, Nie Y, Pei D, Deng S, Chen J, Zhou Y, Duan H, Chen Q, Long E. Outpatient reception via collaboration between nurses and a large language model: a randomized controlled trial. Nature Medicine 2024, 1-8. PMID: 39009780, DOI: 10.1038/s41591-024-03148-7.Peer-Reviewed Original ResearchAltmetricConceptsRandomized controlled trialsNurse-led sessionsPrimary care concernsSingle-center randomized controlled trialCollaborative modelHealthcare experiencesCare concernsPatient queriesMedical careImprove communicationReducing negative emotionsNursesHospital workflowSecondary outcomesMedical CenterLanguage modelSatisfaction feedbackReal-world deploymentProportion of queriesNegative emotionsAudio corpusHuman effortCommunication systemsPatientsCareAn Updated Simplified Severity Scale for Age-Related Macular Degeneration, Incorporating Reticular Pseudodrusen: Age-Related Eye Disease Study Report No. 42
Agrón E, Domalpally A, Chen Q, Lu Z, Chew E, Keenan T, Groups A. An Updated Simplified Severity Scale for Age-Related Macular Degeneration, Incorporating Reticular Pseudodrusen: Age-Related Eye Disease Study Report No. 42. Ophthalmology 2024 PMID: 38657840, DOI: 10.1016/j.ophtha.2024.04.011.Peer-Reviewed Original ResearchCitationsAltmetricConceptsAge-Related Eye Disease StudyProgression to late AMDReticular pseudodrusenLate AMDFive-year ratesProgression rateAge-related macular degenerationSeverity ScaleEye Disease StudyClinical trial cohortIncrease prognostic accuracyPost hoc analysisMacular degenerationAREDS2Prognostic accuracyTrial cohortRisk featuresHoc analysisRisk categorizationPseudodrusenAge-relatedBaselineDisease StudyRiskExternal validationPubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge
Wei C, Allot A, Lai P, Leaman R, Tian S, Luo L, Jin Q, Wang Z, Chen Q, Lu Z. PubTator 3.0: an AI-powered literature resource for unlocking biomedical knowledge. Nucleic Acids Research 2024, 52: w540-w546. PMID: 38572754, PMCID: PMC11223843, DOI: 10.1093/nar/gkae235.Peer-Reviewed Original ResearchCitationsAltmetricConceptsState-of-the-art AI techniquesState-of-the-artComplex information needsAdvanced search capabilitiesPairs queriesEntity relationsRetrieval qualitySearch capabilityAI techniquesLiterature resourcesPubTatorInformation needsPubMed abstractsBiomedical literatureOnline interfaceLarge-scale analysisGenetic variantsBiomedical knowledgeAPIScientific discoveryComprehensive setChatGPTQueryVerifiabilityRetrievalDetection of reticular pseudodrusen on optical coherence tomography images
Elsawy A, Keenan T, Agron E, Chen Q, Chew E, Lu Z. Detection of reticular pseudodrusen on optical coherence tomography images. Progress In Biomedical Optics And Imaging 2024, 12926: 1292632-1292632-5. DOI: 10.1117/12.3007014.Peer-Reviewed Original ResearchConceptsAge-related macular degenerationSD-OCT scansAge-Related Eye Disease Study 2Detect reticular pseudodrusenReticular pseudodrusenSD-OCTFundus autofluorescenceVolumetric spectral-domain optical coherence tomographySpectral-domain optical coherence tomographySubretinal drusenoid depositsOptical coherence tomography imagesPredictors of progressionOptical coherence tomographyReceiver characteristic operating curvesDrusenoid depositsMacular degenerationOCT studiesCoherence tomographyDisease featuresTomography imagesOperating curvePseudodrusenAge-relatedClassification networkMulti-taskingAdvancing entity recognition in biomedicine via instruction tuning of large language models
Keloth V, Hu Y, Xie Q, Peng X, Wang Y, Zheng A, Selek M, Raja K, Wei C, Jin Q, Lu Z, Chen Q, Xu H. Advancing entity recognition in biomedicine via instruction tuning of large language models. Bioinformatics 2024, 40: btae163. PMID: 38514400, PMCID: PMC11001490, DOI: 10.1093/bioinformatics/btae163.Peer-Reviewed Original ResearchCitationsAltmetricConceptsNamed Entity RecognitionSequence labeling taskNatural language processingBiomedical NER datasetsLanguage modelNER datasetsEntity recognitionLabeling taskText generationField of natural language processingBiomedical NERFew-shot learning capabilityReasoning tasksMulti-domain scenariosDomain-specific modelsEnd-to-endMinimal fine-tuningSOTA performanceF1 scoreHealthcare applicationsBiomedical entitiesBiomedical domainLanguage processingMulti-taskingPubMedBERT modelOphthalmic care may not align with patient need: An analysis on state-wide patient needs and provider density between 2008 and 2022
Gilson A, Chen Q, Adelman R. Ophthalmic care may not align with patient need: An analysis on state-wide patient needs and provider density between 2008 and 2022. International Journal Of Medical Informatics 2024, 185: 105411. PMID: 38492409, PMCID: PMC11047060, DOI: 10.1016/j.ijmedinf.2024.105411.Peer-Reviewed Original ResearchConceptsProvider densityPatient needsDensity of ophthalmologistsOphthalmological careHealthcare availabilityResources patientsPractice locationOphthalmologic termsPatient interestOphthalmic carePatient informationImplementation strategiesPatient's desireCareRetinal specialistsEducational backgroundOphthalmologistsPatientsOphthalmologyTrends dataNeedsHealthcareGoogle Trends dataDemographic elementsProvidersGeneGPT: augmenting large language models with domain tools for improved access to biomedical information
Jin Q, Yang Y, Chen Q, Lu Z. GeneGPT: augmenting large language models with domain tools for improved access to biomedical information. Bioinformatics 2024, 40: btae075. PMID: 38341654, PMCID: PMC10904143, DOI: 10.1093/bioinformatics/btae075.Peer-Reviewed Original ResearchCitationsConceptsAPI callsWeb APIsLanguage modelState-of-the-art performanceMulti-hop questionsState-of-the-artDomain-specific toolsDecoding algorithmNational Center for Biotechnology InformationGPT-3Biomedical informationDatabase utilizationExperimental resultsAPITaskDomain toolsLearningChatGPTSpecialized knowledgeInformationLanguageGenomic questionsAlgorithmDatasetBiotechnology InformationImproving 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, ocad259. PMID: 38281112, 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 model
2023
A deep network DeepOpacityNet for detection of cataracts from color fundus photographs
Elsawy A, Keenan T, Chen Q, Thavikulwat A, Bhandari S, Quek T, Goh J, Tham Y, Cheng C, Chew E, Lu Z. A deep network DeepOpacityNet for detection of cataracts from color fundus photographs. Communications Medicine 2023, 3: 184. PMID: 38104223, PMCID: PMC10725427, DOI: 10.1038/s43856-023-00410-w.Peer-Reviewed Original ResearchAltmetricConceptsColor fundus photographyAnterior segment photographsSlit-lamp examinationEye Disease StudyPosterior subcapsular cataractColor fundus photographsAREDS2 participantsCataract presenceSingapore EpidemiologyDetection of cataractOphthalmology clinicFundus photographyFundus photographsSubcapsular cataractCenter gradingCataractOphthalmologistsDisease StudyBlood vesselsNuclear cataractPerson evaluationAREDS2ClinicEpidemiologyDiagnosisOpportunities and challenges for ChatGPT and large language models in biomedicine and health
Tian S, Jin Q, Yeganova L, Lai P, Zhu Q, Chen X, Yang Y, Chen Q, Kim W, Comeau D, Islamaj R, Kapoor A, Gao X, Lu Z. Opportunities and challenges for ChatGPT and large language models in biomedicine and health. Briefings In Bioinformatics 2023, 25: bbad493. PMID: 38168838, PMCID: PMC10762511, DOI: 10.1093/bib/bbad493.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsLarge language modelsLanguage modelSensitive patient dataBiomedical information retrievalText generation tasksInformation retrievalPrivacy concernsDomain expertsInformation extractionText summarizationBiomedical domainArt methodsDiverse applicationsPrevious stateBiomedical researchersGeneration taskPatient dataSuch methodsTaskDistinct complexityGeneration capabilityExtensive literature surveySummarizationRecent rapid progressChallenges
Academic Achievements and Community Involvement
honor National Library of Medicine Honor Award
National AwardNational Institutes of HealthDetails12/31/2023honor National Library of Medicine Data Science and Informatics Mentor Awards
National AwardNational Institutes of HealthDetails07/01/2023United Stateshonor Summer Research Mentor Award
National AwardNational Institutes of HealthDetails07/01/2023honor Fellows Award for Research Excellence
National AwardNational Institutes of HealthDetails05/01/2023honor Summer Research Mentor Award
National AwardNational Institutes of HealthDetails07/01/2022