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Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms
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非線形力学およびグラフ理論的EEG特徴を用いたクロスドメインMCI検出のための解釈可能な特徴変換フレームワーク

Hadi Azizpour Lindi, Reza Shalbaf, Ahmad Shalbaf

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    PubMed
    まとめ

    アルツハイマー病（AD）の予防には、軽度認知障害（MCI）の早期発見が不可欠です。本研究では、EEG由来のエントロピーおよびグラフ特徴量とTransformerネットワークを組み合わせることで、MCIと健常対照者を効果的に区別できることを示しています。

    キーワード:
    軽度認知障害アルツハイマー病脳波Transformerネットワーク特徴量エンジニアリング解釈可能なAI

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