2023
AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning
Luo L, Wei C, Lai P, Leaman R, Chen Q, Lu Z. AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning. Bioinformatics 2023, 39: btad310. PMID: 37171899, PMCID: PMC10212279, DOI: 10.1093/bioinformatics/btad310.Peer-Reviewed Original ResearchConceptsDeep learningEntity recognitionTraining dataEntity typesLabeling training dataNatural language textText mining tasksSignificant domain expertiseMulti-task learningMining tasksInformation extractionBioNER taskDomain expertiseBiomedical entitiesIndependent tasksSource codeBenchmark tasksLanguage textBiomedical textArt approachesAccurate annotationExternal dataData scarcityTaskLearning
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 countsBioSentVec: 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 databaseSemanticsBioWordVec, improving biomedical word embeddings with subword information and MeSH
Zhang Y, Chen Q, Yang Z, Lin H, Lu Z. BioWordVec, improving biomedical word embeddings with subword information and MeSH. Scientific Data 2019, 6: 52. PMID: 31076572, PMCID: PMC6510737, DOI: 10.1038/s41597-019-0055-0.Peer-Reviewed Original ResearchConceptsWord embeddingsSubword informationWord representationsBiomedical natural language processingNatural language processingMultiple NLP tasksBiomedical word embeddingsInformation retrievalUnlabeled textBiomedical textText miningBiomedical domainLanguage processingNLP tasksStructured resourcesChallenging taskPrevious stateBenchmarking resultsLarge corpusEmbeddingWord levelBioWordVecSuch informationTaskInformation