2023
Prediction of Brain Metastases Development in Patients With Lung Cancer by Explainable Artificial Intelligence From Electronic Health Records
Li Z, Li R, Zhou Y, Rasmy L, Zhi D, Zhu P, Dono A, Jiang X, Xu H, Esquenazi Y, Zheng W. Prediction of Brain Metastases Development in Patients With Lung Cancer by Explainable Artificial Intelligence From Electronic Health Records. JCO Clinical Cancer Informatics 2023, 7: e2200141. PMID: 37018650, PMCID: PMC10281421, DOI: 10.1200/cci.22.00141.Peer-Reviewed Original ResearchConceptsBrain metastasesExplainable artificial intelligenceFeature attribution methodsLung cancerEHR dataArtificial intelligenceCerner Health Facts databaseBM developmentExplainable artificial intelligence approachBrain metastasis developmentHealth Facts databaseElectronic health record dataRecurrent neural network modelArtificial intelligence approachHealth record dataModel decision processStructured EHR dataNeural network modelDecision processAttribution methodsHigh-quality cohortElectronic health recordsPrompt treatmentMetastasis developmentIntelligence approach
2022
Assessment of Electronic Health Record for Cancer Research and Patient Care Through a Scoping Review of Cancer Natural Language Processing
Wang L, Fu S, Wen A, Ruan X, He H, Liu S, Moon S, Mai M, Riaz I, Wang N, Yang P, Xu H, Warner J, Liu H. Assessment of Electronic Health Record for Cancer Research and Patient Care Through a Scoping Review of Cancer Natural Language Processing. JCO Clinical Cancer Informatics 2022, 6: e2200006. PMID: 35917480, PMCID: PMC9470142, DOI: 10.1200/cci.22.00006.Peer-Reviewed Original ResearchEvaluation of mCODE Coverage in EHR: a Scoping Review of Cancer Natural Language Processing
Wang L, Fu S, Wen A, Ruan X, He H, Liu S, Moon S, Mai M, Riaz I, Wang N, Yang P, Xu H, Warner J, Liu H. Evaluation of mCODE Coverage in EHR: a Scoping Review of Cancer Natural Language Processing. 2022, 00: 517-518. DOI: 10.1109/ichi54592.2022.00094.Peer-Reviewed Original Research
2020
Representation of EHR data for predictive modeling: a comparison between UMLS and other terminologies
Rasmy L, Tiryaki F, Zhou Y, Xiang Y, Tao C, Xu H, Zhi D. Representation of EHR data for predictive modeling: a comparison between UMLS and other terminologies. Journal Of The American Medical Informatics Association 2020, 27: 1593-1599. PMID: 32930711, PMCID: PMC7647355, DOI: 10.1093/jamia/ocaa180.Peer-Reviewed Original ResearchConceptsUnified Medical Language SystemRecurrent neural networkNeural networkPrediction performanceLogistic regressionPredictive modelingDeep learningData aggregationElectronic health record dataMachine learningRisk predictionBetter prediction performanceDengue hemorrhagic feverHealth record dataEHR dataCancer predictionLarge vocabularyDifferent tasksPredictive modelHeart failureDiabetes patientsPancreatic cancerClinical dataHemorrhagic feverICD-9
2019
Discovery of Noncancer Drug Effects on Survival in Electronic Health Records of Patients With Cancer: A New Paradigm for Drug Repurposing
Wu Y, Warner J, Wang L, Jiang M, Xu J, Chen Q, Nian H, Dai Q, Du X, Yang P, Denny J, Liu H, Xu H. Discovery of Noncancer Drug Effects on Survival in Electronic Health Records of Patients With Cancer: A New Paradigm for Drug Repurposing. JCO Clinical Cancer Informatics 2019, 3: cci.19.00001. PMID: 31141421, PMCID: PMC6693869, DOI: 10.1200/cci.19.00001.Peer-Reviewed Original ResearchConceptsVanderbilt University Medical CenterCancer survivalMayo ClinicDrug repurposingNoncancer drugsElectronic health record dataCancer registry dataEHR dataClinical trial evaluationOverall cancer survivalUniversity Medical CenterHealth record dataElectronic health recordsTreatment of cancerClinical trialsDrug classesRegistry dataMedical CenterDrug effectsSignificant associationLongitudinal EHRNew indicationsPatientsCancerHealth records
2014
Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortality
Xu H, Aldrich M, Chen Q, Liu H, Peterson N, Dai Q, Levy M, Shah A, Han X, Ruan X, Jiang M, Li Y, St Julien J, Warner J, Friedman C, Roden D, Denny J. Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortality. Journal Of The American Medical Informatics Association 2014, 22: 179-191. PMID: 25053577, PMCID: PMC4433365, DOI: 10.1136/amiajnl-2014-002649.Peer-Reviewed Original ResearchConceptsType 2 diabetes patientsElectronic health recordsCancer patientsCancer mortalityDiabetes patientsEHR dataNon-diabetic cancer patientsCox proportional hazards modelDrug exposure informationOral hypoglycemic medicationsCharlson Comorbidity IndexNon-diabetic patientsUse of metforminCancer diagnosisHealth recordsSite-specific cancersBody mass indexProportional hazards modelVanderbilt University Medical CenterUniversity Medical CenterLarge electronic health recordHypoglycemic medicationsCause mortalityComorbidity indexInsulin useChapter 12 Linking Genomic and Clinical Data for Discovery and Personalized Care
Denny J, Xu H. Chapter 12 Linking Genomic and Clinical Data for Discovery and Personalized Care. 2014, 395-424. DOI: 10.1016/b978-0-12-401678-1.00012-9.Peer-Reviewed Original ResearchElectronic health recordsEHR dataNatural language processingSuch algorithmsLanguage processingDecision supportPhenotype algorithmsIdeal repositoryHealth recordsNumber of challengesRepositoryAlgorithmClinical notesClinical careClinical documentationGenomic dataResult dataAccurate caseDNA biobanksEarly demonstration projectsHealth care qualityClinical recordsMedication recordsClinical dataTool
2011
Extracting and integrating data from entire electronic health records for detecting colorectal cancer cases.
Xu H, Fu Z, Shah A, Chen Y, Peterson N, Chen Q, Mani S, Levy M, Dai Q, Denny J. Extracting and integrating data from entire electronic health records for detecting colorectal cancer cases. AMIA Annual Symposium Proceedings 2011, 2011: 1564-72. PMID: 22195222, PMCID: PMC3243156.Peer-Reviewed Original ResearchConceptsEntire electronic health recordElectronic health recordsNatural language processingHealth recordsStructured EHR dataMachine learningText dataNarrative text dataF-measureLanguage processingClinical narrativesEHR dataSuch tasksColorectal cancerDetection methodConcept identificationCohort of patientsColorectal cancer casesVanderbilt University HospitalCase detection methodsClinical notesCRC patientsCRC casesUniversity HospitalCancer cases