2024
Simple autonomous agents can enhance creative semantic discovery by human groups
Ueshima A, Jones M, Christakis N. Simple autonomous agents can enhance creative semantic discovery by human groups. Nature Communications 2024, 15: 5212. PMID: 38890368, PMCID: PMC11189566, DOI: 10.1038/s41467-024-49528-y.Peer-Reviewed Original ResearchComputational reconstruction of mental representations using human behavior
Caplette L, Turk-Browne N. Computational reconstruction of mental representations using human behavior. Nature Communications 2024, 15: 4183. PMID: 38760341, PMCID: PMC11101448, DOI: 10.1038/s41467-024-48114-6.Peer-Reviewed Original ResearchConceptsMental representationsGoal of cognitive scienceVisual featuresNeural networkMultiple visual conceptsDeep neural networksConceptual representationCognitive scienceVisual conceptsSemantic spaceSemantic featuresHuman behaviorParticipantsNetworkRepresentationStimuliBehaviorFeaturesImagesComputer reconstructionTask
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
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