5 citations · 6 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Artificial Open World for Evaluating AGI: a Conceptual Design
Bowen Xu, Quansheng Ren
How to evaluate Artificial General Intelligence (AGI) is a critical problem that is discussed and unsolved for a long period. In the research of narrow AI, this seems not a severe…