2021
LitSuggest: a web-based system for literature recommendation and curation using machine learning
Allot A, Lee K, Chen Q, Luo L, Lu Z. LitSuggest: a web-based system for literature recommendation and curation using machine learning. Nucleic Acids Research 2021, 49: w352-w358. PMID: 33950204, PMCID: PMC8262723, DOI: 10.1093/nar/gkab326.Peer-Reviewed Original ResearchMeSH KeywordsCOVID-19Data CurationHealthcare DisparitiesHumansInternetLiver NeoplasmsMachine LearningPublicationsSoftwareConceptsNatural language processingWeb-based systemQuery methodSearch systemSearch queriesMachine learningWeb serverCuration servicesAdvanced machineUser projectsLanguage processingClassification resultsTraining corpusSingle interfaceUsersBiomedical researchersCollaborative analysisHigh accuracyLiterature recommendationsPubMed articlesMachineCurationComputational methodsSpecialized knowledgeKeywords
2020
LitCovid: an open database of COVID-19 literature
Chen Q, Allot A, Lu Z. LitCovid: an open database of COVID-19 literature. Nucleic Acids Research 2020, 49: d1534-d1540. PMID: 33166392, PMCID: PMC7778958, DOI: 10.1093/nar/gkaa952.Peer-Reviewed Original ResearchMeSH KeywordsCOVID-19Data CurationData MiningDatabases, FactualHumansInternetMachine LearningPandemicsPublicationsPubMedSARS-CoV-2ConceptsSerious information overloadCuration workflowData miningInformation overloadCollected articlesInformation needsOpen databaseManual curationNews articlesCOVID-19 literatureLiterature resourcesRapid growthUsersCOVID-19 researchMiningWorkflowAlgorithmCurationDate scientific informationDatabaseInformationGeneral publicResourcesAccessTextDeep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical records
Chen Q, Du J, Kim S, Wilbur W, Lu Z. Deep learning with sentence embeddings pre-trained on biomedical corpora improves the performance of finding similar sentences in electronic medical records. BMC Medical Informatics And Decision Making 2020, 20: 73. PMID: 32349758, PMCID: PMC7191680, DOI: 10.1186/s12911-020-1044-0.Peer-Reviewed Original ResearchMeSH KeywordsData MiningDeep LearningElectronic Health RecordsHumansInformation Storage and RetrievalLanguageMachine LearningPubMedConceptsEnd deep learning modelEncoder networkDeep learning modelsSentence embeddingsBiomedical corporaLearning modelRandom forestTraditional machineText mining applicationsDeep learning approachSimilar sentencesMachine learning modelsHigh performanceMining applicationsRelated datasetsClinical notesLearning approachSentence semanticsPubMed abstractsChallenge taskEnsembled modelBest submissionSentence pairsNetworkTest set
2019
ML-Net: multi-label classification of biomedical texts with deep neural networks
Du J, Chen Q, Peng Y, Xiang Y, Tao C, Lu Z. ML-Net: multi-label classification of biomedical texts with deep neural networks. Journal Of The American Medical Informatics Association 2019, 26: 1279-1285. PMID: 31233120, PMCID: PMC7647240, DOI: 10.1093/jamia/ocz085.Peer-Reviewed Original ResearchConceptsMulti-label classificationML-NetBiomedical textEnd deep learning frameworkMulti-label text classificationDeep learning frameworkDeep neural networksTraditional machineDocument contextFeature engineeringText classificationTextual documentsMachine learningNovel endLearning frameworkPrediction networkIndividual classifiersNeural networkHuman effortTarget documentsF-measureArt methodsPrediction mechanismContextual informationLabel counts