AI-enhanced EEG and source localization for retrospective analysis of Alzheimer’s disease and mild cognitive impairment

Background Distinguishing Alzheimer’s disease (AD) and mild cognitive impairment (MCI) through electroencephalography (EEG) remains challenging due to subtle neurophysiological differences.Method This study establishes an AI-enhanced EEG framework integrating Random Forest classification with sLORET...

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Detalles Bibliográficos

Principais autores:	Mengsheng Du, Hongqi Li, Xiaojiang Huang, Yunxiang Shi, Yao An, Zhaoyang Chen, Shuai Gao, Huiqing Zhang, Yao Yao
Formato:	Artigo
Idioma:	Inglês
Publicado:	Taylor & Francis Group 2025-12-01
Series:	Brain-Apparatus Communication
Assuntos:	Electroencephalogram (EEG) analysis Alzheimer’s disease (AD;), mild cognitive impairment (MCI;), random Forest
Acceso en liña:	https://www.tandfonline.com/doi/10.1080/27706710.2025.2604895
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