2019
Deep learning in clinical natural language processing: a methodical review
Wu S, Roberts K, Datta S, Du J, Ji Z, Si Y, Soni S, Wang Q, Wei Q, Xiang Y, Zhao B, Xu H. Deep learning in clinical natural language processing: a methodical review. Journal Of The American Medical Informatics Association 2019, 27: 457-470. PMID: 31794016, PMCID: PMC7025365, DOI: 10.1093/jamia/ocz200.Peer-Reviewed Original ResearchConceptsNatural language processingClinical natural language processingDeep learningLanguage processingComputing Machinery Digital LibraryInformation extraction tasksMedical informatics communityComputational Linguistics anthologyRecurrent neural networkDigital librariesText classificationElectronic health recordsExtraction taskEntity recognitionWord2vec embeddingsNeural networkRelation extractionNLP communityNLP researchInformatics communitySpecific tasksHealth recordsNLP problemLearningClinical domains
2012
A study of transportability of an existing smoking status detection module across institutions.
Liu M, Shah A, Jiang M, Peterson N, Dai Q, Aldrich M, Chen Q, Bowton E, Liu H, Denny J, Xu H. A study of transportability of an existing smoking status detection module across institutions. AMIA Annual Symposium Proceedings 2012, 2012: 577-86. PMID: 23304330, PMCID: PMC3540509.Peer-Reviewed Original ResearchConceptsDetection moduleNatural language processing systemsKnowledge Extraction SystemEMR dataRule-based classifierClinical Text AnalysisHighest F-measureLanguage processing systemElectronic medical recordsF-measureLevels of classificationProcessing systemSpecific tasksText analysisClassifierDesirable performanceModuleModest effortExtraction systemCTAKESSmoking moduleMachineSystemTaskClassification