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Updated: Jun 15, 2026

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
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Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

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マルチサイトfMRI研究におけるサイト変性を克服する:機械学習モデルの一般化強化のための自動エンコーダーフレームワーク

Fahad Almuqhim1,2, Fahad Saeed3

  • 1Knight Foundation School of Computing and Information Sciences (KFSCIS), Florida International University, Miami, FL, USA.

Neuroinformatics
|September 2, 2025
PubMed
まとめ

オートエンコーダーは,マルチサイト機能磁気共鳴画像 (fMRI) データを効果的に調和させ,機械学習モデルの汎用性を改善します. この新しいアプローチは,サイト固有の変動性とデータ漏れを軽減し,臨床アプリケーションの信頼性を高めます.

キーワード:
分類するデータの調和ディープラーニングFMRI多サイト

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