Deep Learning of Multimodal Features Derived from Raw Polysomnography for Cognitive Impairment Prediction
The results support the potential of routine polysomnography for opportunistic cognitive-risk assessment and fused the epoch-level features with whole-night aggregated features and demographics using a temporal convolutional network for binary prediction of cognitive impairment.
Somesh Saini, S. Thanaviratananich, M. Araujo
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