2022
A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora
Li J, Wei Q, Ghiasvand O, Chen M, Lobanov V, Weng C, Xu H. A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora. BMC Medical Informatics And Decision Making 2022, 22: 235. PMID: 36068551, PMCID: PMC9450226, DOI: 10.1186/s12911-022-01967-7.Peer-Reviewed Original ResearchConceptsPre-trained language modelsNER taskUnstructured textEntity recognitionLanguage modelNatural language processing techniquesClinical trial eligibility criteriaLanguage processing techniquesData augmentation resultsData augmentation approachDomain-specific corpusBetter performanceTransformer modelCross-validation showMultiple data sourcesEligibility criteria textBiomedical domainEmbedding modelsNER performanceAugmentation approachContextual embeddingsMeaningful informationEvaluation resultsSuch documentsProcessing techniques
2021
Study of Pre-trained Language Models for Named Entity Recognition in Clinical Trial Eligibility Criteria from Multiple Corpora
Li J, Wei Q, Ghiasvand O, Chen M, Lobanov V, Weng C, Xu H. Study of Pre-trained Language Models for Named Entity Recognition in Clinical Trial Eligibility Criteria from Multiple Corpora. 2021, 00: 511-512. DOI: 10.1109/ichi52183.2021.00095.Peer-Reviewed Original ResearchClinical trial eligibility criteriaClinical trial eligibilityTrial eligibility criteriaEligibility criteria textTrial eligibilityEligibility criteria