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March 3, 2026
STCWTNet: Spatio-temporal channel-wise transformer network for interpretable cross-subject mild cognitive impairment detection using EEG signals
YL
Yin Liu
Chongqing University of Posts and Telecommunications
JD
Jiaojiao Deng
Chongqing University of Posts and Telecommunications
RX
Runyi Xu
Tsinghua University
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Puntos clave
Mild cognitive impairment detection achieved high accuracy with EEG signals—indicating potential for early diagnosis.
Accuracy metrics reached over 90% in identifying cognitive impairment from EEG signals in the tested population.
Analysis employed a novel spatio-temporal transformer approach with channel-wise attention mechanisms for better performance.
Supports the use of EEG data as a reliable tool for diagnosing mild cognitive impairment, though broader testing may be needed.
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STCWTNet: Spatio-temporal channel-wise transformer network for interpretable cross-subject mild cognitive impairment detection using EEG signals | Synapse
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Liu et al. (Tue,) studied this question.
synapsesocial.com/papers/69a75ad3c6e9836116a212c8
https://doi.org/https://doi.org/10.1016/j.bspc.2026.109564