From Tokenization to Self-Supervision: Building a High-Performance Information Extraction System for Chemical Reactions in Patents
Wang J, Ren Y, Zhang Z, Xu H, Zhang Y. From Tokenization to Self-Supervision: Building a High-Performance Information Extraction System for Chemical Reactions in Patents. Frontiers In Research Metrics And Analytics 2021, 6: 691105. PMID: 35005421, PMCID: PMC8727901, DOI: 10.3389/frma.2021.691105.Peer-Reviewed Original ResearchEvent extractionEntity recognitionNatural language processing techniquesAccurate information extractionInformation extraction systemLanguage processing techniquesKnowledge-based rulesInformation extractionAutomatic toolEnd systemArt resultsSemantic rolesLanguage modelSelf-SupervisionFree textChemical patentsSubtask 1Reaction extractionDifferent semantic rolesHybrid approachEvent triggersProcessing techniquesSubtasksTokenizationHigh performanceCOVID-19 SignSym: a fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model
Wang J, Abu-El-Rub N, Gray J, Pham H, Zhou Y, Manion F, Liu M, Song X, Xu H, Rouhizadeh M, Zhang Y. COVID-19 SignSym: a fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model. Journal Of The American Medical Informatics Association 2021, 28: 1275-1283. PMID: 33674830, PMCID: PMC7989301, DOI: 10.1093/jamia/ocab015.Peer-Reviewed Original ResearchConceptsNatural language processing toolsCommon data modelLanguage processing toolsElectronic health recordsClinical natural language processing toolsData modelDeep learning-based modelProcessing toolsOMOP Common Data ModelPattern-based rulesObservational Medical Outcomes Partnership Common Data ModelLearning-based modelsSpecific information needsUse casesNLP toolsClinical textFree textExtensive evaluationDownloadable packageInformation needsHybrid approachResearch communityHealth recordsData sourcesHigh performance