Development and validation of a multimodal automatic interictal epileptiform discharge detection model: a prospective multi-center study

Development and validation of a multimodal automatic interictal epileptiform discharge detection model: a prospective multi-center study

Abstract Background Visual identification of interictal epileptiform discharge (IED) is expert-biased and time-consuming. Accurate automated IED detection models can facilitate epilepsy diagnosis. This study aims to develop a multimodal IED detection model (vEpiNetV2) and conduct a multi-center vali...

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Main Authors: Nan Lin, Lian Li, Weifang Gao, Peng Hu, Gonglin Yuan, Heyang Sun, Fang Qi, Lin Wang, Shengsong Wang, Zi Liang, Haibo He, Yisu Dong, Zaifen Gao, Xiaoqiu Shao, Liying Cui, Qiang Lu
Format: Article
Language:English
Published: BMC 2025-08-01
Series:BMC Medicine
Subjects:
Interictal epileptiform discharge detection
Deep learning
Multi-center validation
Multimodal
EEG
Video
Online Access:https://doi.org/10.1186/s12916-025-04316-3
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https://doi.org/10.1186/s12916-025-04316-3

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