Seizure prediction
1개 벤치마크 · 논문 68편 · 이 태스크의 논문 보기 →
Benchmarks
Most implemented
Learning Optimized Risk Scores
SlimSeiz: Efficient Channel-Adaptive Seizure Prediction Using a Mamba-Enhanced Network
A library of quantitative markers of seizure severity
Seizure Detection and Prediction by Parallel Memristive Convolutional Neural Networks
Interpretable EEG seizure prediction using a multiobjective evolutionary algorithm
Searching for waveforms on spatially-filtered epileptic ECoG
Papers
CLSP-REQA: A Real-Time Quality-Aware Closed-Loop Seizure Prediction Framework with Mamba-BiLSTM and Confidence-Gated Intervention
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 real-world deployment, and the overwhel…
Seizure predictionDomain AdaptationEpileptic Seizure Prediction Using Patient-Adaptive Transformer Networks
Epileptic seizure prediction from electroencephalographic (EEG) recordings remains challenging due to strong inter-patient variability and the complex temporal structure of neural signals. This paper presents a patient-a…
Representation LearningTemporal SequencesSeizure predictionEEG-Titans: Long-Horizon Seizure Forecasting via Dual-Branch Attention and Neural Memory
Accurate epileptic seizure prediction from electroencephalography (EEG) remains challenging because pre-ictal dynamics may span long time horizons while clinically relevant signatures can be subtle and transient. Many de…
Seizure predictionHCFT: Hierarchical Convolutional Fusion Transformer for EEG Decoding
Electroencephalography (EEG) decoding requires models that can effectively extract and integrate complex temporal, spectral, and spatial features from multichannel signals. To address this challenge, we propose a lightwe…
Representation LearningSeizure predictionEeg DecodingA Patient-Independent Neonatal Seizure Prediction Model Using Reduced Montage EEG and ECG
Neonates are highly susceptible to seizures, often leading to short or long-term neurological impairments. However, clinical manifestations of neonatal seizures are subtle and often lead to misdiagnoses. This increases t…
Seizure predictionTransfer LearningSeizure DetectionEpileptic Seizure Detection and Prediction from EEG Data: A Machine Learning Approach with Clinical Validation
In recent years, machine learning has become an increasingly powerful tool for supporting seizure detection and monitoring in epilepsy care. Traditional approaches focus on identifying seizures only after they begin, whi…
Seizure predictionSeizure Detection