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Updated: Feb 28, 2026

Performing Behavioral Tasks in Subjects with Intracranial Electrodes
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多分岐畳み込みニューラルネットワークと頭蓋内EEG高周波振動が術後発作転帰を予測する

Madhumathi Devaraj1, Yihe Chen2, Shuang Wang2

  • 1Department of Neurology, Stony Brook University, Stony Brook, USA.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
|February 25, 2026
PubMed
まとめ

畳み込みニューラルネットワーク（CNN）は、高周波振動（HFO）、神経解剖学、および手術データを分析することにより、てんかん手術後の発作からの自由を正確に予測する。このAIツールは、仮想切除をテストすることで手術転帰を改善する可能性がある。

キーワード:
生物医学信号処理脳マッピング畳み込みニューラルネットワーク（CNN）ディープラーニングてんかん手術高周波振動（HFO）頭蓋内脳波（iEEG）機械学習神経画像発作予測

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Seizures: Classification

Epilepsy is primarily characterized by unpredictable seizures, either provoked by an identifiable factor, such as injury or illness, or unprovoked, occurring spontaneously without apparent cause.
Seizures are typically classified into two main categories: focal and generalized seizures.
Focal Seizures
Focal seizures originate from specific regions of the brain. These seizures are further sub-classified into two types:
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