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Shijian Li

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Open access Sep 2026

BRAINet: a brain-region-aware interaction network for EEG-based diagnosis of disorders of consciousness

Objective. Reliable assessment and stratification of disorders of consciousness (DOC) is essential for patient care and clinical treatment planning. Electroencephalography (EEG) provides a non-invasive approach to measure neural activity and has shown promise in DOC assessment. However, most existing EEG-based approach...

Hao-Xiang Chen, Sha Zhao, Jie Yu et al. · 0 citations
Review Open access Sep 2026

EEG Biomarkers for Affective Disorders Diagnosis: An Evaluation and Validation Study

Electroencephalography (EEG) provides real‐time, dynamic insights into brain function, making it a valuable tool for the screening, diagnosis, and treatment of affective disorders. The use of EEG‐derived features as biomarkers for affective disorder diagnosis has attracted growing attention. In this work, we introduce...

Sha Zhao, Yi-Tian Liu, Jiquan Wang et al. · 0 citations
#artificial intelligence Preprint Aug 2026

BrainBench: Benchmarking Large Language Models for Comprehensive EEG Understanding

A unified benchmark for comprehensive, instruction-conditioned EEG understanding is introduced and results vary substantially across models, subsets, difficulty levels, and execution paradigms, showing that EEG competence depends on the model and its operationalization.

Yangxuan Zhou, Yu-Ning Chen, Chentian Wu et al. · 0 citations

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