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Updated: May 6, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

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TASNet：進行性軽度認知障害の分類のためのトリモーダル注意スケールロバスト適応型融合フレームワーク

Hongliang Zhu1, Limei Zhang1, Lu Yang1

  • 1School of Computer and Artificial Intelligence, Shandong Jianzhu University, Jinan, Shandong, China.

Journal of neuroscience methods
|February 25, 2026
PubMed
まとめ

この研究では、脳画像と液体バイオマーカーを使用して進行性軽度認知障害（pMCI）を予測するための新しいフレームワークであるTASNetを紹介します。TASNetは、安定MCI（sMCI）からpMCIを区別する際に高い精度を達成し、早期アルツハイマー病の介入に役立ちます。

キーワード:
アルツハイマー病注意機構深層学習軽度認知障害マルチモーダル融合

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