2020
COVID-19 TestNorm: A tool to normalize COVID-19 testing names to LOINC codes
Dong X, Li J, Soysal E, Bian J, DuVall S, Hanchrow E, Liu H, Lynch K, Matheny M, Natarajan K, Ohno-Machado L, Pakhomov S, Reeves R, Sitapati A, Abhyankar S, Cullen T, Deckard J, Jiang X, Murphy R, Xu H. COVID-19 TestNorm: A tool to normalize COVID-19 testing names to LOINC codes. Journal Of The American Medical Informatics Association 2020, 27: 1437-1442. PMID: 32569358, PMCID: PMC7337837, DOI: 10.1093/jamia/ocaa145.Peer-Reviewed Original ResearchConceptsElectronic health recordsLOINC codesSecondary useRule-based toolOnline web applicationOpen-source packageCritical data elementsWeb applicationData networksEnd usersData elementsIndependent test setHealth recordsTest setKey challengesData normalizationCritical resourcesTest namesRoutine clinical practice dataCodeClinical practice dataCoronavirus disease 2019COVID-19 diagnostic testsToolDevelopers
2011
Anomaly and signature filtering improve classifier performance for detection of suspicious access to EHRs.
Kim J, Grillo J, Boxwala A, Jiang X, Mandelbaum R, Patel B, Mikels D, Vinterbo S, Ohno-Machado L. Anomaly and signature filtering improve classifier performance for detection of suspicious access to EHRs. AMIA Annual Symposium Proceedings 2011, 2011: 723-31. PMID: 22195129, PMCID: PMC3243249.Peer-Reviewed Original ResearchConceptsSuspicious accessAccess recordsRule-based techniquesMachine learning methodsConstruction of classifiersAnomaly detectionInformative instancesLearning methodsSymbolic clusteringClassifier performanceSignature detectionIndependent test setInappropriate accessTest setEHRFiltering methodIntegrated filtering strategyFiltering strategyClassifierFilteringNegative rateFalse negative rateAccessDetectionClustering