2024
FedFSA: Hybrid and federated framework for functional status ascertainment across institutions
Fu S, Jia H, Vassilaki M, Keloth V, Dang Y, Zhou Y, Garg M, Petersen R, St Sauver J, Moon S, Wang L, Wen A, Li F, Xu H, Tao C, Fan J, Liu H, Sohn S. FedFSA: Hybrid and federated framework for functional status ascertainment across institutions. Journal Of Biomedical Informatics 2024, 152: 104623. PMID: 38458578, PMCID: PMC11005095, DOI: 10.1016/j.jbi.2024.104623.Peer-Reviewed Original ResearchNatural language processingElectronic health recordsStatus informationInformation extractionFunctional status informationRule-based information extractionFederated learning frameworkPrivate local dataNatural language processing frameworkHealthcare sitesPatient's functional statusMultiple healthcare institutionsFederated learningPyTorch libraryConcept normalizationBERT modelLearning frameworkCollaborative development effortsCorpus annotationLanguage processingHealthcare institutionsFunctional statusPredictor of health outcomesActivities of daily livingNatural language processing performance
2020
Relation Extraction from Clinical Narratives Using Pre-trained Language Models.
Wei Q, Ji Z, Si Y, Du J, Wang J, Tiryaki F, Wu S, Tao C, Roberts K, Xu H. Relation Extraction from Clinical Narratives Using Pre-trained Language Models. AMIA Annual Symposium Proceedings 2020, 2019: 1236-1245. PMID: 32308921, PMCID: PMC7153059.Peer-Reviewed Original ResearchConceptsPre-trained language modelsNatural language processingLanguage modelRE tasksNLP tasksClinical narrativesRecent deep learning methodsDeep learning methodsClinical NLP tasksRelation extraction taskTraditional word embeddingsTraditional machineExtraction taskArt performanceRelation extractionBERT modelLanguage processingLearning methodsWord embeddingsShared TaskPrevious stateBiomedical literatureDifferent implementationsTaskOpen domain