2023
FinFax: Fast Interpretation of Fax with NLP
Anjum O, Chen L, Denlinger R, Anam E, Dongsheng Y, Wooldridge C, Citardi M, Zhang J, Xu H, Jiang X. FinFax: Fast Interpretation of Fax with NLP. 2023, 1-2. DOI: 10.1145/3584371.3613019.Peer-Reviewed Original ResearchEnd systemCritical medical informationElectronic health record systemsHealth record systemsReal-life applicationsVital clinical dataFirst endManual processingInformation exchangeHealthcare organizationsOverall workflowHealth recordsMedical informationRecord systemWorkflowFinal outputFast interpretationFaxAcademic environmentInformationPertinent informationMultiple solutionsProcessingReal-life hospital settingsNLP
2021
Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality
Tortolero G, Brown M, Sharma S, de Oliveira Otto M, Yamal J, Aguilar D, Gunther M, Mofleh D, Harris R, John J, de Vries P, Ramphul R, Serbo D, Kiger J, Banerjee D, Bonvino N, Merchant A, Clifford W, Mikhail J, Xu H, Murphy R, Wei Q, Vahidy F, Morrison A, Boerwinkle E. Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality. PLOS ONE 2021, 16: e0247235. PMID: 34081724, PMCID: PMC8174716, DOI: 10.1371/journal.pone.0247235.Peer-Reviewed Original ResearchConceptsBody mass indexCOVID-19 patientsRisk factorsTobacco useCOVID-19 fatalitiesHealth information exchangeRace/ethnicityCOVID-19Laboratory risk factorsNumber of comorbiditiesCOVID-19 cohortMultivariable logistic regressionImportant risk factorPotential risk factorsCOVID-19 outcomesFormer tobacco usersTobacco use historyLarge health information exchangeMass indexElectronic health record systemsUnfavorable outcomeClinical dataTobacco usersOutcome analysisElectronic health information
2018
Extraction of BI-RADS findings from breast ultrasound reports in Chinese using deep learning approaches
Miao S, Xu T, Wu Y, Xie H, Wang J, Jing S, Zhang Y, Zhang X, Yang Y, Zhang X, Shan T, Wang L, Xu H, Wang S, Liu Y. Extraction of BI-RADS findings from breast ultrasound reports in Chinese using deep learning approaches. International Journal Of Medical Informatics 2018, 119: 17-21. PMID: 30342682, DOI: 10.1016/j.ijmedinf.2018.08.009.Peer-Reviewed Original ResearchConceptsLearning-based methodsBreast ultrasound reportsElectronic health record systemsTraditional machine learning-based methodsDeep learning-based approachDeep learning-based methodsNatural language processing methodsMachine learning-based methodsDeep learning technologyConditional random field algorithmDeep learning approachLanguage processing methodsLearning-based approachUltrasound reportsBreast cancer researchRule-based methodHealth record systemsBreast radiology reportsLearning technologyNLP approachLearning approachField algorithmDetailed clinical informationWide adoptionRecord systemToward 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
2015
A Preliminary Study of Clinical Abbreviation Disambiguation in Real Time
Wu Y, Denny J, Rosenbloom S, Miller R, Giuse D, Song M, Xu H. A Preliminary Study of Clinical Abbreviation Disambiguation in Real Time. Applied Clinical Informatics 2015, 06: 364-374. PMID: 26171081, PMCID: PMC4493336, DOI: 10.4338/aci-2014-10-ra-0088.Peer-Reviewed Original ResearchConceptsElectronic health record systemsUser studyClinical documentation systemNatural language processing systemsClinical NLP systemsPreliminary user studyAbbreviation recognitionExtra time costLanguage processing systemWSD methodHealth record systemsDocumentation systemPrototype applicationWord sense disambiguation methodNLP systemsCorrect sensesNote generationPrototype systemClinical sentencesCost of timeClinical documentsDocument entryDisambiguation moduleSense disambiguation methodHealthcare records
2013
A prototype application for real-time recognition and disambiguation of clinical abbreviations
Wu Y, Denny J, Rosenbloom S, Miller R, Giuse D, Song M, Xu H. A prototype application for real-time recognition and disambiguation of clinical abbreviations. 2013, 7-8. DOI: 10.1145/2512089.2512096.Peer-Reviewed Original ResearchElectronic health record systemsPrototype applicationClinical documentation systemNatural language processing systemsClinical abbreviationsClinical NLP systemsReal-time recognitionLanguage processing systemAverage response timeHealth record systemsDocumentation systemResponse timeWord sense disambiguation methodNLP systemsNote generationPrototype systemClinical documentsSense disambiguation methodHealthcare recordsProcessing systemAbbreviation disambiguationCard systemDisambiguation methodAbbreviation recognitionSystem design