2011
Detecting abbreviations in discharge summaries using machine learning methods.
Wu Y, Rosenbloom S, Denny J, Miller R, Mani S, Giuse D, Xu H. Detecting abbreviations in discharge summaries using machine learning methods. AMIA Annual Symposium Proceedings 2011, 2011: 1541-9. PMID: 22195219, PMCID: PMC3243185.Peer-Reviewed Original ResearchConceptsNatural language processingMachine learning methodsHighest F-measureF-measureClinical natural language processingLexical resourcesClinical abbreviationsTraining setPre-defined featuresRandom forest classifierDomain expertsML algorithmsML classifiersLanguage processingVoting schemeLearning methodsDischarge summariesForest classifierTest setClassifierCorpus-based methodSetResourcesAlgorithmAbbreviations
2007
A study of abbreviations in clinical notes.
Xu H, Stetson P, Friedman C. A study of abbreviations in clinical notes. AMIA Annual Symposium Proceedings 2007, 2007: 821-5. PMID: 18693951, PMCID: PMC2655910.Peer-Reviewed Original ResearchMeSH KeywordsAbbreviations as TopicDecision TreesHumansMEDLINENatural Language ProcessingUnified Medical Language SystemConceptsUnified Medical Language SystemNatural language processing systemsLanguage processing systemNarrative clinical notesDetection methodClinical notesDifferent knowledge sourcesSense inventoryDomain expertsNLP systemsCorrect sensesDecision supportText corporaKnowledge sourcesError detectionProcessing systemBiomedical literatureStudy of abbreviationsLanguage systemPatient informationAmbiguity rateBetter detection methodsDatabaseAnnotationAbbreviations