2024
Attention-based acoustic feature fusion network for depression detection
Xu X, Wang Y, Wei X, Wang F, Zhang X. Attention-based acoustic feature fusion network for depression detection. Neurocomputing 2024, 601: 128209. DOI: 10.1016/j.neucom.2024.128209.Peer-Reviewed Original ResearchFeature fusion networkFusion networkDepression detectionAdvanced machine learning paradigmsDeep neural networksMachine learning paradigmLSTM-attention mechanismSpeech databaseFeature modelSpeech featuresNeural networkAbundance of informationBoost performanceLearning paradigmImproved detection methodAuditory dataAcoustic featuresDetection methodFeature processingAdjustment moduleNetworkLSTM-AttentionResearch directionsEffective detectionFeatures
2021
Preliminary Evaluation of Phenotypic Features from Clinical Interactions
Barron D, Heisig S, Agurto C, Norel R, Quagan B, Powers A, Baker J, Constable T, Cecchi G, Krystal J. Preliminary Evaluation of Phenotypic Features from Clinical Interactions. Journal Of Pain 2021, 22: 594. DOI: 10.1016/j.jpain.2021.03.068.Peer-Reviewed Original ResearchCommon software toolsChannel audioSoftware toolsFeature dataGaze featuresLack of granularityFeature spaceAction unitsSpeech featuresTraining biasesDigital featuresCross-validation approachMovement featuresClinical progress notesFacial featuresLinguistic featuresPreliminary evaluationAudioPhenotypic informationPatient trajectoriesFeaturesGranularityCameraAlgorithmProgress notes
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