2024
NLP Applications—Other Biomedical Texts
Roberts K, Xu H, Demner Fushman D. NLP Applications—Other Biomedical Texts. Cognitive Informatics In Biomedicine And Healthcare 2024, 429-444. DOI: 10.1007/978-3-031-55865-8_15.Peer-Reviewed Original Research
2022
ClinicalLayoutLM: A Pre-trained Multi-modal Model for Understanding Scanned Document in Electronic Health Records
Wei Q, Zuo X, Anjum O, Hu Y, Denlinger R, Bernstam E, Citardi M, Xu H. ClinicalLayoutLM: A Pre-trained Multi-modal Model for Understanding Scanned Document in Electronic Health Records. 2022, 00: 2821-2827. DOI: 10.1109/bigdata55660.2022.10020569.Peer-Reviewed Original ResearchOptical character recognitionMulti-modal modelElectronic health recordsClinical documentsNatural language processing tasksInformation extraction technologyPre-trained modelsHealth recordsLanguage processing tasksInformation extractionImage informationF1 scoreCharacter recognitionLayout analysisProcessing tasksMulti-modal approachClinical corpusBaseline modelDocumentsOpen domainTaskExtraction technologyClinical operationsDifferent categoriesTextNatural Language Processing
Xu H, Roberts K. Natural Language Processing. Cognitive Informatics In Biomedicine And Healthcare 2022, 213-234. DOI: 10.1007/978-3-031-09108-7_7.Peer-Reviewed Original ResearchNatural language processingLanguage processingElectronic health recordsBiomedical domainBiomedical natural language processingCommon NLP tasksNarrative textNLP tasksBiomedical articlesClinical documentsNLP fieldTextHealth recordsLarge amountBasic conceptsBibliographic databasesProcessingTaskArticleDocumentsDomainChapterDatabaseInformationAttention
2018
Clinical text annotation - what factors are associated with the cost of time?
Wei Q, Franklin A, Cohen T, Xu H. Clinical text annotation - what factors are associated with the cost of time? AMIA Annual Symposium Proceedings 2018, 2018: 1552-1560. PMID: 30815201, PMCID: PMC6371268.Peer-Reviewed Original ResearchConceptsAnnotation timeClinical textNatural language processing modelsClinical corpusIndividual user behaviorEntity recognition taskLanguage processing modelsPractice of annotationCharacteristics of sentencesClinical Text AnnotationText annotationsUser behaviorIndividual usersCost of timeActive learning researchRecognition taskLearning researchProcessing modelCost modelAnnotationUsersLimited workCorpusTextTaskAdapting Word Embeddings from Multiple Domains to Symptom Recognition from Psychiatric Notes.
Zhang Y, Li H, Wang J, Cohen T, Roberts K, Xu H. Adapting Word Embeddings from Multiple Domains to Symptom Recognition from Psychiatric Notes. AMIA Joint Summits On Translational Science Proceedings 2018, 2017: 281-289. PMID: 29888086, PMCID: PMC5961810.Peer-Reviewed Original ResearchWord embeddingsClinical textTarget domainSource domainNatural language processing techniquesLanguage processing techniquesMultiple word embeddingsBaseline methodsBiomedical literatureFirst workProcessing techniquesEmbeddingPsychiatric notesMultiple domainsExperimental resultsDifferent weightsSuch informationImportant topicRecognitionDifferent approachesWikipediaInformationPersonalizationDomainText
2015
Recognizing Disjoint Clinical Concepts in Clinical Text Using Machine Learning-based Methods.
Tang B, Chen Q, Wang X, Wu Y, Zhang Y, Jiang M, Wang J, Xu H. Recognizing Disjoint Clinical Concepts in Clinical Text Using Machine Learning-based Methods. AMIA Annual Symposium Proceedings 2015, 2015: 1184-93. PMID: 26958258, PMCID: PMC4765674.Peer-Reviewed Original ResearchDomain adaptation for semantic role labeling of clinical text
Zhang Y, Tang B, Jiang M, Wang J, Xu H. Domain adaptation for semantic role labeling of clinical text. Journal Of The American Medical Informatics Association 2015, 22: 967-979. PMID: 26063745, PMCID: PMC4986662, DOI: 10.1093/jamia/ocu048.Peer-Reviewed Original Research
2013
Analyzing differences between chinese and english clinical text: a cross-institution comparison of discharge summaries in two languages.
Wu Y, Lei J, Wei W, Tang B, Denny J, Rosenbloom S, Miller R, Giuse D, Zheng K, Xu H. Analyzing differences between chinese and english clinical text: a cross-institution comparison of discharge summaries in two languages. 2013, 192: 662-6. PMID: 23920639, PMCID: PMC4957806.Peer-Reviewed Original ResearchConceptsNatural language processing toolsEnglish clinical textClinical textLanguage processing toolsChinese clinical textCultural differencesMajor clinical componentsTextWestern institutionsInpatient discharge summariesCross-country collaborationDocument levelProcessing toolsClinical documentsLanguageUS institutionsUsesUnprecedented amountValuable insightsInstitutionsDocumentsChinaWorldwide adoptionEMR dataCollaboration