2024
OncoSplicing 3.0: an updated database for identifying RBPs regulating alternative splicing events in cancers
Zhang Y, Liu K, Xu Z, Li B, Wu X, Fan R, Yao X, Wu H, Duan C, Gong Y, Chen K, Zeng J, Li L, Xu H. OncoSplicing 3.0: an updated database for identifying RBPs regulating alternative splicing events in cancers. Nucleic Acids Research 2024, gkae1098. PMID: 39558172, DOI: 10.1093/nar/gkae1098.Peer-Reviewed Original ResearchRNA-binding proteinsAlternative splicing eventsAS eventsSplicing eventsAlternative splicingPotential RNA-binding proteinsRegulate alternative splicing eventsTCGA cancersRNA-binding motifRNA-seq dataRegulate gene expressionMRNA expression dataECLIP-seqGTEx tissuesENCODE projectAbnormal alternative splicingIntron sequencesSplicing analysisRNA-seqExpression dataProtein complexesMinigene constructsSplicingGene expressionPerturbation experimentsSirtuin1 Suppresses Calcium Oxalate Nephropathy via Inhibition of Renal Proximal Tubular Cell Ferroptosis Through PGC‐1α‐mediated Transcriptional Coactivation
Duan C, Li B, Liu H, Zhang Y, Yao X, Liu K, Wu X, Mao X, Wu H, Xu Z, Zhong Y, Hu Z, Gong Y, Xu H. Sirtuin1 Suppresses Calcium Oxalate Nephropathy via Inhibition of Renal Proximal Tubular Cell Ferroptosis Through PGC‐1α‐mediated Transcriptional Coactivation. Advanced Science 2024, e2408945. PMID: 39498889, DOI: 10.1002/advs.202408945.Peer-Reviewed Original ResearchCrystal-induced kidney injuryPGC-1aSingle-cell transcriptome sequencingNuclear factor erythroid 2-related factor 2Resistance to ferroptosisKidney injuryTranscriptional coactivatorTranscriptome sequencingRenal tubular epithelial cell injuryCalcium oxalate nephropathyPromoter regionRenal proximal tubular cellsTubular epithelial cell injuryEpithelial cell injuryProximal tubular cellsFactor erythroid 2-related factor 2Erythroid 2-related factor 2Oxalate nephropathyCell ferroptosisSIRT1Crystal nephropathyFerroptosisTubular cellsGPX4 transcriptionTherapeutic targetSEETrials: Leveraging large language models for safety and efficacy extraction in oncology clinical trials
Lee K, Paek H, Huang L, Hilton C, Datta S, Higashi J, Ofoegbu N, Wang J, Rubinstein S, Cowan A, Kwok M, Warner J, Xu H, Wang X. SEETrials: Leveraging large language models for safety and efficacy extraction in oncology clinical trials. Informatics In Medicine Unlocked 2024, 50: 101589. PMID: 39493413, PMCID: PMC11530223, DOI: 10.1016/j.imu.2024.101589.Peer-Reviewed Original ResearchAntibody-drug conjugatesOverall response rateMultiple myelomaF1 scoreCAR-TComplete responseBispecific antibodiesComparative performance analysisClinical trial studyClinical trial outcomesLanguage modelAccurate data extractionTherapy subgroupFine granularityOncology clinical trialsAdverse eventsClinical decision-makingPerformance analysisClinical trialsInnovative therapiesDiverse therapiesClinical trial abstractsCancer domainData elementsTherapyImproving tabular data extraction in scanned laboratory reports using deep learning models
Li Y, Wei Q, Chen X, Li J, Tao C, Xu H. Improving tabular data extraction in scanned laboratory reports using deep learning models. Journal Of Biomedical Informatics 2024, 159: 104735. PMID: 39393477, DOI: 10.1016/j.jbi.2024.104735.Peer-Reviewed Original ResearchTree edit distanceOptical character recognitionTable recognitionDeep learning modelsAverage recallAverage precisionState-of-the-art deep learning modelsLearning modelsRegion-of-interest detectionState-of-the-artCharacter recognitionDetection evaluationTree editingTabular dataImpressive resultsLab test resultsLaboratory test reportsClinical documentationRecognitionLaboratory reportsHealthcare organizationsClinical data analysisDecision makingClinical decision makingTest reportsAugmenting biomedical named entity recognition with general-domain resources
Yin Y, Kim H, Xiao X, Wei C, Kang J, Lu Z, Xu H, Fang M, Chen Q. Augmenting biomedical named entity recognition with general-domain resources. Journal Of Biomedical Informatics 2024, 159: 104731. PMID: 39368529, DOI: 10.1016/j.jbi.2024.104731.Peer-Reviewed Original ResearchBioNER datasetsMulti-task learningNER datasetsEntity typesBiomedical datasetsBaseline modelGeneral domain datasetsBiomedical language modelNeural network-basedYield performance improvementsBioNER modelsEntity recognitionBiomedical corporaHuman annotatorsLabel ambiguityLanguage modelTransfer learningF1 scoreBioNERHuman effortNetwork-basedBiomedical resourcesPerformance improvementDatasetSuperior performanceAscle—A Python Natural Language Processing Toolkit for Medical Text Generation: Development and Evaluation Study
Yang R, Zeng Q, You K, Qiao Y, Huang L, Hsieh C, Rosand B, Goldwasser J, Dave A, Keenan T, Ke Y, Hong C, Liu N, Chew E, Radev D, Lu Z, Xu H, Chen Q, Li I. Ascle—A Python Natural Language Processing Toolkit for Medical Text Generation: Development and Evaluation Study. Journal Of Medical Internet Research 2024, 26: e60601. PMID: 39361955, PMCID: PMC11487205, DOI: 10.2196/60601.Peer-Reviewed Original ResearchConceptsNatural language processingNatural language processing toolkitQuestion-answering taskLanguage modelText generationText processingDomain-specific language modelsNatural language processing functionsMinimal programming expertiseText generation tasksMedical knowledge graphMachine translation tasksROUGE-L scoreDomain-specific challengesAll-in-one solutionROUGE-LText summarizationBLEU scoreKnowledge graphMachine translationUnstructured textQuestion-answeringHugging FaceProcessing toolkitLanguage processingRelation extraction using large language models: a case study on acupuncture point locations
Li Y, Peng X, Li J, Zuo X, Peng S, Pei D, Tao C, Xu H, Hong N. Relation extraction using large language models: a case study on acupuncture point locations. Journal Of The American Medical Informatics Association 2024, 31: 2622-2631. PMID: 39208311, PMCID: PMC11491641, DOI: 10.1093/jamia/ocae233.Peer-Reviewed Original ResearchAcupuncture point locationsAcupoint locationLocation of acupointsClinical decision supportAcupuncture knowledgeAcupuncture trainingAcupuncture therapyAcupunctureAcupointsComplementary medicineEducational moduleWestern Pacific RegionInformatics applicationsDecision supportScoresGenerative Pre-trained TransformerWHO standardsF1 scoreLanguage modelPacific regionWHODomain-specific fine-tuningTrainingStudyMicro-averaged F1 scoreBalancing the efforts of chart review and gains in PRS prediction accuracy: An empirical study
Lei Y, Christian Naj A, Xu H, Li R, Chen Y. Balancing the efforts of chart review and gains in PRS prediction accuracy: An empirical study. Journal Of Biomedical Informatics 2024, 157: 104705. PMID: 39134233, DOI: 10.1016/j.jbi.2024.104705.Peer-Reviewed Original ResearchAlzheimer's Disease Genetics ConsortiumChart reviewPRS modelCase-control datasetGenetic association analysisGenetics ConsortiumPhenotype misclassificationSimulated phenotypesPhenotypic dataAssociation analysisEstimation of associated parametersBias reduction methodMedian thresholdPhenotypeMisclassification rateOriginal phenotypeDiverse arrayChartsMisclassificationGenotypesReviewEffects of biasBiasPrediction modelPRSRe: Iver Nordentoft, Sia Viborg Lindskrog, Karin Birkenkamp-Demtröder, et al. Whole-genome Mutational Analysis for Tumor-informed Detection of Circulating Tumor DNA in Patients with Urothelial Carcinoma. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2024.05.014
Wu X, Yao X, Chen Z, Xu H. Re: Iver Nordentoft, Sia Viborg Lindskrog, Karin Birkenkamp-Demtröder, et al. Whole-genome Mutational Analysis for Tumor-informed Detection of Circulating Tumor DNA in Patients with Urothelial Carcinoma. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2024.05.014. European Urology 2024 PMID: 39117526, DOI: 10.1016/j.eururo.2024.07.021.Peer-Reviewed Original ResearchLeveraging error-prone algorithm-derived phenotypes: Enhancing association studies for risk factors in EHR data
Lu Y, Tong J, Chubak J, Lumley T, Hubbard R, Xu H, Chen Y. Leveraging error-prone algorithm-derived phenotypes: Enhancing association studies for risk factors in EHR data. Journal Of Biomedical Informatics 2024, 157: 104690. PMID: 39004110, DOI: 10.1016/j.jbi.2024.104690.Peer-Reviewed Original ResearchElectronic health recordsElectronic health record dataKaiser Permanente WashingtonEHR-derived phenotypesAssociation studiesHealth recordsColon cancer recurrencePhenotyping errorsComputable phenotypeRisk factorsCancer recurrenceMultiple phenotypesReduce biasImprove estimation accuracySimulation studyBias reductionKaiserReduction of biasBiasEstimation accuracyAssociationStudyOutcomesRiskEstimation efficiencyDevelop and validate a computable phenotype for the identification of Alzheimer's disease patients using electronic health record data
He X, Wei R, Huang Y, Chen Z, Lyu T, Bost S, Tong J, Li L, Zhou Y, Li Z, Guo J, Tang H, Wang F, DeKosky S, Xu H, Chen Y, Zhang R, Xu J, Guo Y, Wu Y, Bian J. Develop and validate a computable phenotype for the identification of Alzheimer's disease patients using electronic health record data. Alzheimer's & Dementia Diagnosis Assessment & Disease Monitoring 2024, 16: e12613. PMID: 38966622, PMCID: PMC11220631, DOI: 10.1002/dad2.12613.Peer-Reviewed Original ResearchElectronic health record dataElectronic health recordsComputable phenotypeHealth record dataManual chart reviewHealth recordsAlzheimer's diseaseDiagnosis codesRecord dataChart reviewUTHealthAlzheimer's disease patientsUniversity of MinnesotaAD diagnosisAD identificationDisease patientsPatientsAlzheimerAD patientsDemographicsDiagnosisDiseaseCodeDataUniversityExtracting Systemic Anticancer Therapy and Response Information From Clinical Notes Following the RECIST Definition
Zuo X, Kumar A, Shen S, Li J, Cong G, Jin E, Chen Q, Warner J, Yang P, Xu H. Extracting Systemic Anticancer Therapy and Response Information From Clinical Notes Following the RECIST Definition. JCO Clinical Cancer Informatics 2024, 8: e2300166. PMID: 38885475, DOI: 10.1200/cci.23.00166.Peer-Reviewed Original ResearchConceptsNatural language processingDomain-specific language modelsNatural language processing systemsInformation extraction systemRule-based moduleNarrative clinical textsNLP tasksEntity recognitionText normalizationAssertion classificationLanguage modelInformation extractionClinical textElectronic health recordsLearning-basedClinical notesLanguage processingTest setSystem performanceHealth recordsResponse extractionTime-consumingAnticancer therapyInformationAssessment informationRelation Extraction
Devarakonda M, Raja K, Xu H. Relation Extraction. Cognitive Informatics In Biomedicine And Healthcare 2024, 101-135. DOI: 10.1007/978-3-031-55865-8_5.Peer-Reviewed Original ResearchNamed Entity Recognition
Devarakonda M, Raja K, Xu H. Named Entity Recognition. Cognitive Informatics In Biomedicine And Healthcare 2024, 79-99. DOI: 10.1007/978-3-031-55865-8_4.Peer-Reviewed Original ResearchNLP Applications—Other Biomedical Texts
Roberts K, Xu H, Demner Fushman D. NLP Applications—Other Biomedical Texts. Cognitive Informatics In Biomedicine And Healthcare 2024, 429-444. DOI: 10.1007/978-3-031-55865-8_15.Peer-Reviewed Original ResearchIntroduction to Natural Language Processing of Clinical Text
Demner Fushman D, Xu H. Introduction to Natural Language Processing of Clinical Text. Cognitive Informatics In Biomedicine And Healthcare 2024, 3-11. DOI: 10.1007/978-3-031-55865-8_1.Peer-Reviewed Original ResearchNatural language processingLanguage processingComplex language processingBiomedical natural language processingClinical natural language processingLanguage generation tasksClinical language processingBiomedical language processingLanguage modelClinical textGeneration taskMachine learningDelivery of informationClinical languageLanguageMedical Concept Normalization
Xu H, Demner Fushman D, Hong N, Raja K. Medical Concept Normalization. Cognitive Informatics In Biomedicine And Healthcare 2024, 137-164. DOI: 10.1007/978-3-031-55865-8_6.Peer-Reviewed Original ResearchConcept normalizationDeep learning-based techniquesMedical concept normalizationLearning-based techniquesContemporary machine learningRule-based methodologyAnnotated corpusNLP systemsMachine learningComputing applicationsBiomedical terminologiesNormalization approachStandardized terminologyOntologyTaskLearningDevelopment of Clinical NLP Systems
Xu H, Demner Fushman D. Development of Clinical NLP Systems. Cognitive Informatics In Biomedicine And Healthcare 2024, 301-324. DOI: 10.1007/978-3-031-55865-8_11.Peer-Reviewed Original ResearchKamino: A Scalable Architecture to Support Medical AI Research Using Large Real World Data
Lin F, Young P, He H, Huang J, Gagne R, Rice D, Price N, Byron W, Hu Y, Felker D, Button W, Meeker D, Hsiao A, Xu H, Torre C, Schulz W. Kamino: A Scalable Architecture to Support Medical AI Research Using Large Real World Data. 2024, 00: 500-504. DOI: 10.1109/ichi61247.2024.00072.Peer-Reviewed Original ResearchElectronic health recordsAI researchNatural language processing tasksElectronic health record dataLanguage processing tasksComputing resource managementLarge-scale data retrievalMedical AI researchLeveraging electronic health recordsStandard data modelKubernetes orchestratorScalable architectureProcessing tasksResource allocation systemsSecurity considerationsAccess managementData retrievalData modelArchitectural solutionsOMOP CDMReal World DataWorld DataHealth recordsOMOPDataMapping Study Variables to Common Data Elements Using GPT for Sheets: Towards Standardized Data Collection and Sharing
Ram P, Hong N, Xu H, Jiang X. Mapping Study Variables to Common Data Elements Using GPT for Sheets: Towards Standardized Data Collection and Sharing. 2024, 00: 320-325. DOI: 10.1109/ichi61247.2024.00048.Peer-Reviewed Original Research