BioSentVec: creating sentence embeddings for biomedical texts
Chen Q, Peng Y, Lu Z. BioSentVec: creating sentence embeddings for biomedical texts. 2019, 00: 1-5. DOI: 10.1109/ichi.2019.8904728.Peer-Reviewed Original ResearchNatural language processing systemsSentence embeddingsBiomedical textAdvanced deep learning methodsDeep learning methodsBiomedical text miningBiomedical word embeddingsLanguage processing systemPre-trained sentence encodersText miningArt performanceLearning methodsSentence semanticsSentence encoderWord embeddingsProcessing systemBenchmarking resultsEmbeddingSimilarity taskClinical notesTaskEssential partGeneral domainsClinical databaseSemanticsOverview 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