2023
Identifying suicide documentation in clinical notes through zero‐shot learning
Workman T, Goulet J, Brandt C, Warren A, Eleazer J, Skanderson M, Lindemann L, Blosnich J, O'Leary J, Zeng‐Treitler Q. Identifying suicide documentation in clinical notes through zero‐shot learning. Health Science Reports 2023, 6: e1526. PMID: 37706016, PMCID: PMC10495736, DOI: 10.1002/hsr2.1526.Peer-Reviewed Original ResearchZero-shot learningDeep neural networksTraining dataNeural networkZero-shot learning modelData sparsity issueIdentical training dataTrue positive instancesClinical notesDeep learningDocument contentSparsity issueManual annotationTarget labelsLearning modelSemantic spaceTraining samplesPositive instancesWord featuresTraining casesBaseline modelAuxiliary informationTerms of areaLearningProbability threshold
2020
A Prototype Application to Identify LGBT Patients in Clinical Notes
Workman T, Goulet J, Brandt C, Skanderson M, Wang R, Warren A, Eleazer J, Gordon K, Zeng-Treitler Q. A Prototype Application to Identify LGBT Patients in Clinical Notes. 2020, 00: 4270-4275. DOI: 10.1109/bigdata50022.2020.9378109.Peer-Reviewed Original ResearchElectronic health record notesPrototype applicationLGBT patientsRule-based patternLarge data sourcesBinary classification taskRecord notesData scientistsMachine learningClassification taskPositive predictive valueData researchData sourcesTest setClinical relevancePredictive valueHealthcare providersPatientsClinical notesHealth disparitiesLittle workDisproportional burdenApplicationsTaskLearning