2022
Discovering novel drug-supplement interactions using SuppKG generated from the biomedical literature
Schutte D, Vasilakes J, Bompelli A, Zhou Y, Fiszman M, Xu H, Kilicoglu H, Bishop J, Adam T, Zhang R. Discovering novel drug-supplement interactions using SuppKG generated from the biomedical literature. Journal Of Biomedical Informatics 2022, 131: 104120. PMID: 35709900, PMCID: PMC9335448, DOI: 10.1016/j.jbi.2022.104120.Peer-Reviewed Original ResearchConceptsUnified Medical Language SystemComprehensive knowledge graphDomain terminologyKnowledge graphSemantic relationsNatural language processing technologyLanguage processing technologyNLP toolsDownstream tasksF1 scoreSemantic relationshipsDiscovery patternsPubMed abstractsLimited coverageBiomedical literatureProcessing technologyLanguage systemSemRepDietary supplement informationManual reviewNovel methodologyGraphNodesDomainTask
2018
Toward a normalized clinical drug knowledge base in China—applying the RxNorm model to Chinese clinical drugs
Wang L, Zhang Y, Jiang M, Wang J, Dong J, Liu Y, Tao C, Jiang G, Zhou Y, Xu H. Toward a normalized clinical drug knowledge base in China—applying the RxNorm model to Chinese clinical drugs. Journal Of The American Medical Informatics Association 2018, 25: 809-818. PMID: 29635469, PMCID: PMC7647010, DOI: 10.1093/jamia/ocy020.Peer-Reviewed Original ResearchConceptsChinese patent drugDrug knowledge basePatent drugsClinical drugsChemical drugsChinese drugsManual reviewChinese patent medicineElectronic health record systemsClinical dataChina's health insurance systemHealth record systemsDrug AdministrationHealth insurance systemDrug informationDrugsPatent medicineDrug namesRecord systemPharmacy system
2017
Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing
Redman J, Natarajan Y, Hou J, Wang J, Hanif M, Feng H, Kramer J, Desiderio R, Xu H, El-Serag H, Kanwal F. Accurate Identification of Fatty Liver Disease in Data Warehouse Utilizing Natural Language Processing. Digestive Diseases And Sciences 2017, 62: 2713-2718. PMID: 28861720, DOI: 10.1007/s10620-017-4721-9.Peer-Reviewed Original ResearchConceptsData warehouseFatty liver diseaseLanguage processingNatural language processingLiver diseaseF-measureAlgorithm developmentVeterans Affairs Corporate Data WarehouseMagnetic resonance imaging reportsOutcomes of patientsAlgorithmExpert radiologistsValidation methodElectronic medical recordsCorporate Data WarehouseWarehouseAbdominal ultrasoundManual reviewHepatic steatosisMedical recordsRandom national sampleClinical studiesLarge cohortComputerized tomographyImaging reports
2010
Extracting timing and status descriptors for colonoscopy testing from electronic medical records
Denny J, Peterson J, Choma N, Xu H, Miller R, Bastarache L, Peterson N. Extracting timing and status descriptors for colonoscopy testing from electronic medical records. Journal Of The American Medical Informatics Association 2010, 17: 383-388. PMID: 20595304, PMCID: PMC2995656, DOI: 10.1136/jamia.2010.004804.Peer-Reviewed Original ResearchConceptsElectronic medical recordsMedical recordsColorectal cancer screening ratesCRC screening statusCancer screening ratesManual reviewStatus indicatorsHealth services researchersColonoscopy testingEMR notesTypes of CRCScreening statusScreening ratesColonoscopy screeningBilling codesUseful adjunctGold standardElectronic recordsColonoscopyPatientsServices researchersFurther investigationRandom sampleTemporal expression