most citedA dual-system approach for epilepsy diagnosis: integrating mamba-Bi-LSTM architecture with SHAP-based verification

1 citations · 1 across the 3 of their papers we have counts for

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eess.SP2026★ 1 cited

A dual-system approach for epilepsy diagnosis: integrating mamba-Bi-LSTM architecture with SHAP-based verification

Mufeng Chen, Jia Xie, Fuchang Luo +1

This study develops a medical AI-assisted diagnosis system based on deep learning, which provides intelligent diagnostic solutions for epilepsy, a disease that seriously threatens…

eess.SP2026

CG-MambaNet: A spatiotemporal framework for cross-patient epileptic seizure prediction using CNN-GCN-Mamba-BiLSTM with event-level clinical evaluation

Mufeng Chen, Qi Wu, Bingchao Huang +6

Epileptic seizure prediction from scalp EEG is critical for closed-loop neurostimulation therapy. Existing deep-learning methods share two architectural limitations: they model EEG…

eess.SP2026

CLSP-REQA: A Real-Time Quality-Aware Closed-Loop Seizure Prediction Framework with Mamba-BiLSTM and Confidence-Gated Intervention

Mufeng Chen, Qi Wu, Bingchao Huang +4

Reliable seizure prediction is a prerequisite for closed-loop neurostimulation therapy, yet existing methods rarely account for the variability in EEG signal quality encountered in…