2016
Chemical named entity recognition in patents by domain knowledge and unsupervised feature learning
Zhang Y, Xu J, Chen H, Wang J, Wu Y, Prakasam M, Xu H. Chemical named entity recognition in patents by domain knowledge and unsupervised feature learning. Database 2016, 2016: baw049. PMID: 27087307, PMCID: PMC4834204, DOI: 10.1093/database/baw049.Peer-Reviewed Original ResearchConceptsMachine learning-based systemsLearning-based systemConditional Random FieldsDomain knowledgeEntity recognitionMatthews correlation coefficientDrug Named Entity RecognitionBioCreative V challengeInformation extraction systemWord representation featuresUnsupervised feature learningUnsupervised learning algorithmNamed Entity RecognitionSemantic type informationSupport vector machinePrecision-recall curveBrown clusteringFeature learningFeature engineeringUnsupervised featureIndividual subtasksMining systemNER taskLearning algorithmCPD task
2015
Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network.
Wu Y, Jiang M, Lei J, Xu H. Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network. 2015, 216: 624-8. PMID: 26262126, PMCID: PMC4624324.Peer-Reviewed Original ResearchConceptsDeep neural networksLarge unlabeled corpusNamed Entity RecognitionWord embeddingsUnlabeled corpusUnsupervised learningEntity recognitionNeural networkNatural language processing technologyNovel deep learning methodLanguage processing technologyDeep learning methodsUnsupervised feature learningFeature engineering approachImportant healthcare informationChinese clinical textTypes of entitiesFeature learningNER taskClinical textLearning methodsClinical documentsCRF modelHealthcare informationFree text