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
2018
Interactive medical word sense disambiguation through informed learning
Wang Y, Zheng K, Xu H, Mei Q. Interactive medical word sense disambiguation through informed learning. Journal Of The American Medical Informatics Association 2018, 25: 800-808. PMID: 29584896, PMCID: PMC6658868, DOI: 10.1093/jamia/ocy013.Peer-Reviewed Original Research
2014
Integrative Genomics and Computational Systems Medicine
McDermott J, Huang Y, Zhang B, Xu H, Zhao Z. Integrative Genomics and Computational Systems Medicine. BioMed Research International 2014, 2014: 945253. PMID: 25025078, PMCID: PMC4082850, DOI: 10.1155/2014/945253.Peer-Reviewed Original Research
2013
Interdisciplinary dialogue for education, collaboration, and innovation: Intelligent Biology and Medicine in and beyond 2013
Zhang B, Huang Y, McDermott J, Posey R, Xu H, Zhao Z. Interdisciplinary dialogue for education, collaboration, and innovation: Intelligent Biology and Medicine in and beyond 2013. BMC Genomics 2013, 14: s1. PMID: 24564388, PMCID: PMC4042234, DOI: 10.1186/1471-2164-14-s8-s1.Peer-Reviewed Original Research