2021
Benchmarking Effectiveness and Efficiency of Deep Learning Models for Semantic Textual Similarity in the Clinical Domain: Validation Study
Chen Q, Rankine A, Peng Y, Aghaarabi E, Lu Z. Benchmarking Effectiveness and Efficiency of Deep Learning Models for Semantic Textual Similarity in the Clinical Domain: Validation Study. JMIR Medical Informatics 2021, 9: e27386. PMID: 34967748, PMCID: PMC8759018, DOI: 10.2196/27386.Peer-Reviewed Original ResearchSemantic textual similarityConvolutional neural networkDeep learning modelsReal-time applicationsDL modelsSentence pairsNeural networkTextual similarityBERT modelNational Natural Language Processing Clinical ChallengesLearning modelNatural language processingAverage Pearson correlationData setsDifferent similarity levelsInference timeGeneralization capabilityManual annotationLanguage processingPearson correlationEnsemble modelWord orderTime efficiencyNegation termsTraining set
2019
Overview of the BioCreative VI Precision Medicine Track: mining protein interactions and mutations for precision medicine
Doğan R, Kim S, Chatr-aryamontri A, Wei C, Comeau D, Antunes R, Matos S, Chen Q, Elangovan A, Panyam N, Verspoor K, Liu H, Wang Y, Liu Z, Altınel B, Hüsünbeyi Z, Özgür A, Fergadis A, Wang C, Dai H, Tran T, Kavuluru R, Luo L, Steppi A, Zhang J, Qu J, Lu Z. Overview of the BioCreative VI Precision Medicine Track: mining protein interactions and mutations for precision medicine. Database 2019, 2019: bay147. PMID: 30689846, PMCID: PMC6348314, DOI: 10.1093/database/bay147.Peer-Reviewed Original ResearchConceptsRelation extraction taskDocument triage taskBest F-scoreExtraction taskTriage taskKnowledge basesF-scorePubMed documentsArt deep learning methodsText-mining research communityLarge knowledge basesDeep learning methodsText mining systemText mining modelText mining toolsBest average precisionData setsLarge-scale corpusHuman annotationsElectronic health recordsSystem developersBetter recallText miningAverage precisionLearning methods