Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device

Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device

Abstract Mild cognitive impairment (MCI) and dementia pose significant health challenges in aging societies, emphasizing the need for accessible, cost-effective, and noninvasive diagnostic tools. Electroencephalography (EEG) is a promising biomarker, but traditional systems are limited by size, cost...

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Bibliographic Details
Main Authors: Masahiro Hata, Takufumi Yanagisawa, Yuki Miyazaki, Hisaki Omori, Atsuya Hirashima, Yuta Nakagawa, Mitsuhiro Eto, Kenji Yoshiyama, Hideki Kanemoto, Byambadorj Nyamradnaa, Shusuke Yoshimoto, Kotaro Ezure, Shun Takahashi, Manabu Ikeda
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Dementia
Mild cognitive impairment
Alzheimer’s disease
DLB
EEG
Deep learning
Online Access:https://doi.org/10.1038/s41598-025-12526-1
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https://doi.org/10.1038/s41598-025-12526-1

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