Vipina K. Keloth, PhD
Associate Research Scientist in Biomedical Informatics and Data ScienceDownloadHi-Res Photo
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Associate Research Scientist in Biomedical Informatics and Data Science
Biography
Dr. Vipina Keloth is an Associate Research Scientist at the Department of Biomedical Informatics and Data Science at Yale School of Medicine. Previously, she was a Postdoctoral Associate at Yale BIDS and prior to that a Postdoctoral Research Fellow at the School of Biomedical Informatics at the University of Texas Health Science Center at Houston. Vipina graduated with a doctoral degree in Computer Science from New Jersey Institute of Technology (NJIT) in 2021. She has also worked as an assistant lecturer in the Department of Mathematical and Computational Sciences at the National Institute of Technology Karnataka, India. Her research interests lie broadly in the domain of biomedical ontologies/terminologies and clinical and biomedical natural language processing.
Last Updated on May 26, 2025.
Appointments
Biomedical Informatics & Data Science
Associate Research ScientistPrimary
Other Departments & Organizations
Education & Training
- Postdoctoral Associate
- Yale University (2024)
- Postdoctoral Research Fellow
- University of Texas Health Science Center at Houston (2023)
- PhD
- New Jersey Institute of Technology, Computer Science (2021)
- MS
- National Institute of Technology Karnataka, Systems Analysis and Computer Applications (2014)
- MSc
- Mahatma Gandhi University, Computer Applications (2010)
- BS
- Kannur University, Physics (2007)
Research
Overview
Medical Research Interests
Biological Ontologies; Natural Language Processing; Social Determinants of Health
ORCID
0000-0001-6919-1122
Research at a Glance
Yale Co-Authors
Frequent collaborators of Vipina K. Keloth's published research.
Publications Timeline
A big-picture view of Vipina K. Keloth's research output by year.
Research Interests
Research topics Vipina K. Keloth is interested in exploring.
Hua Xu, PhD
Qingyu Chen, PhD
Loren Laine, MD
Hamita Sachar, MD
Karen Wang, MD, MHS
Lucila Ohno-Machado, MD, MBA, PhD
33Publications
362Citations
Biological Ontologies
Social Determinants of Health
Natural Language Processing
Publications
2025
Ontology enrichment using a large language model: Applying lexical, semantic, and knowledge network-based similarity for concept placement
Kollapally N, Geller J, Keloth V, He Z, Xu J. Ontology enrichment using a large language model: Applying lexical, semantic, and knowledge network-based similarity for concept placement. Journal Of Biomedical Informatics 2025, 168: 104865. PMID: 40543734, DOI: 10.1016/j.jbi.2025.104865.Peer-Reviewed Original ResearchConceptsSemantic triplesSeed ontologyHuman expertsLogical axiomsPubMed abstractsSimilarity search techniquesState-of-the-artReal-world conceptsNetwork-based filterLanguage modelSemantic correctnessText corpusNetwork-based searchSource of textDomain viewSearch techniqueNetwork-based similaritySemMedDBOntology toolsOntologyIdentified conceptsSource of conceptsPipelineDomains of social determinants of healthAxiomsDeveloping and sustaining inclusive language in biomedical informatics communications: an AMIA Board of Directors endorsed paper on the Inclusive Language and Context Style Guidelines
Bear Don't Walk O, Haldar S, Wei D, Huang H, Rivera R, Fan J, Keloth V, Leung T, Desai P, Korngiebel D, Grossman Liu L, Pichon A, Subbian V, Solomonides A, Wiley L, Ogunyemi O, Jackson G, Dankwa-Mullan I, Dirks L, Everhart A, Parker A, Iott B, Kronk C, Foraker R, Martin K, Anand T, Volpe S, Yung N, Rizvi R, Lucero R, Bright T. Developing and sustaining inclusive language in biomedical informatics communications: an AMIA Board of Directors endorsed paper on the Inclusive Language and Context Style Guidelines. Journal Of The American Medical Informatics Association 2025, ocaf096. PMID: 40523007, DOI: 10.1093/jamia/ocaf096.Peer-Reviewed Original ResearchAltmetricSocial determinants of health extraction from clinical notes across institutions using large language models
Keloth V, Selek S, Chen Q, Gilman C, Fu S, Dang Y, Chen X, Hu X, Zhou Y, He H, Fan J, Wang K, Brandt C, Tao C, Liu H, Xu H. Social determinants of health extraction from clinical notes across institutions using large language models. Npj Digital Medicine 2025, 8: 287. PMID: 40379919, PMCID: PMC12084648, DOI: 10.1038/s41746-025-01645-8.Peer-Reviewed Original ResearchAltmetricBenchmarking 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 domainTaskBenchmarksBERTInformationPerformanceLLMThe Development Landscape of Large Language Models for Biomedical Applications.
Cao Z, Keloth V, Xie Q, Qian L, Liu Y, Wang Y, Shi R, Zhou W, Yang G, Zhang J, Peng X, Zhen E, Weng R, Chen Q, Xu H. The Development Landscape of Large Language Models for Biomedical Applications. Annual Review Of Biomedical Data Science 2025 PMID: 40169010, DOI: 10.1146/annurev-biodatasci-102224-074736.Peer-Reviewed Original ResearchConceptsLanguage modelTask-specific fine-tuningPrivacy concernsImprove data sharingComputational resourcesSpecialized medical applicationsBiomedical dataData sharingFine-tuningBiomedical literatureTransform healthcareModel accessDevelopment processMedical applicationsMultimodal integrationChatGPTPrivacyApplicationsModel characteristicsTrainingArchitectureLLMMedical researchMedical 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 performanceTextPerformance
2024
Using clinical entity recognition for curating an interface terminology to aid fast skimming of EHRs
Kollapally N, Dehkordi M, Perl Y, Geller J, Deek F, Liu H, Keloth V, Elhanan G, Einstein A, Zhou S. Using clinical entity recognition for curating an interface terminology to aid fast skimming of EHRs. 2024, 00: 6427-6434. DOI: 10.1109/bibm62325.2024.10822845.Peer-Reviewed Original ResearchConceptsElectronic health recordsEntity recognitionVolume of electronic health recordsEHR interoperabilityClinical entity recognitionClinical terminologyNeural network modelClinical NERTransfer learningSNOMED CT conceptsInterface terminologyNetwork modelSNOMED CTHealth recordsHigher granularityCT conceptsOverworked physiciansHealthcare providersDense volumeRecognitionInteroperabilityCurationGranularityCardiology patientsNERDetection of Gastrointestinal Bleeding With Large Language Models to Aid Quality Improvement and Appropriate Reimbursement
Zheng N, Keloth V, You K, Kats D, Li D, Deshpande O, Sachar H, Xu H, Laine L, Shung D. Detection of Gastrointestinal Bleeding With Large Language Models to Aid Quality Improvement and Appropriate Reimbursement. Gastroenterology 2024, 168: 111-120.e4. PMID: 39304088, DOI: 10.1053/j.gastro.2024.09.014.Peer-Reviewed Original ResearchCitationsAltmetricConceptsElectronic health recordsOvert gastrointestinal bleedingGastrointestinal bleedingRecurrent bleedingMachine learning modelsHealth recordsClinically relevant applicationsNursing notesLanguage modelAcute gastrointestinal bleedingQuality improvementLearning modelsDetection of gastrointestinal bleedingReimbursementIdentification of clinical conditionsSeparate hospitalsQuality measuresHospitalBleedingClinical conditionsPatient managementEarly identificationPatientsReimbursement codesCoding algorithmA Study of Biomedical Relation Extraction Using GPT Models.
Zhang J, Wibert M, Zhou H, Peng X, Chen Q, Keloth V, Hu Y, Zhang R, Xu H, Raja K. A Study of Biomedical Relation Extraction Using GPT Models. AMIA Joint Summits On Translational Science Proceedings 2024, 2024: 391-400. PMID: 38827097, PMCID: PMC11141827.Peer-Reviewed Original ResearchCitations543 IDENTIFYING OVERT SIGNS OF ACUTE GASTROINTESTINAL BLEEDING IN THE ELECTRONIC HEALTH RECORD WITH LARGE LANGUAGE MODELS
Zheng N, Keloth V, You K, Li D, Xu H, Laine L, Shung D. 543 IDENTIFYING OVERT SIGNS OF ACUTE GASTROINTESTINAL BLEEDING IN THE ELECTRONIC HEALTH RECORD WITH LARGE LANGUAGE MODELS. Gastroenterology 2024, 166: s-124-s-125. DOI: 10.1016/s0016-5085(24)00776-5.Peer-Reviewed Original ResearchConcepts
Academic Achievements & Community Involvement
Activities
activity American Medical Informatics Association (AMIA)
05/15/2018 - PresentProfessional OrganizationsMemberactivity Journal of Biomedical Informatics
06/30/2021 - PresentJournal ServiceRevieweractivity BMC Supplements
06/01/2021 - PresentJournal ServiceRevieweractivity AMIA DEI Communications Subcommittee
10/28/2021 - PresentProfessional OrganizationsMemberactivity JAMIA Open
04/03/2023 - PresentJournal ServiceReviewer
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