2024
StrokeClassifier: ischemic stroke etiology classification by ensemble consensus modeling using electronic health records
Lee H, Schwamm L, Sansing L, Kamel H, de Havenon A, Turner A, Sheth K, Krishnaswamy S, Brandt C, Zhao H, Krumholz H, Sharma R. StrokeClassifier: ischemic stroke etiology classification by ensemble consensus modeling using electronic health records. Npj Digital Medicine 2024, 7: 130. PMID: 38760474, PMCID: PMC11101464, DOI: 10.1038/s41746-024-01120-w.Peer-Reviewed Original ResearchElectronic health recordsWeighted F1MIMIC-IIIClinical decision support systemsMulti-class classificationNatural language processingMIMIC-III datasetHealth recordsMachine learning classifiersDecision support systemArtificial intelligence toolsVascular neurologistsLearning classifiersBinary classificationCross-validation accuracyLanguage processingMeta-modelIntelligence toolsStroke prevention effortsAcute ischemic strokeStroke etiologySupport systemStroke etiology classificationClassification toolClassifier
2022
Neural Natural Language Processing for unstructured data in electronic health records: A review
Li I, Pan J, Goldwasser J, Verma N, Wong W, Nuzumlalı M, Rosand B, Li Y, Zhang M, Chang D, Taylor R, Krumholz H, Radev D. Neural Natural Language Processing for unstructured data in electronic health records: A review. Computer Science Review 2022, 46: 100511. DOI: 10.1016/j.cosrev.2022.100511.Peer-Reviewed Original ResearchNatural language processingElectronic health recordsLanguage processingDeep learning approachHealth recordsRule-based systemNew neural networkVariety of tasksUnstructured dataUnstructured textKnowledge graphEHR applicationsDigital collectionsNeural networkNLP methodsLearning approachWord embeddingsSurvey paperSecondary useMedical dialogueHealthcare eventsTaskProcessingMultilingualityInterpretability