3 papers
math.DS2026
Detecting seizure onset and offset times using human intelligence: A critical-transitions-based approach
Andrew Flynn, Cian McCafferty, Klaus Lehnertz +4
Most existing seizure detection algorithms require extensive pre-processing of the data and rely on heuristic or currently unexplainable machine learning approaches. These approach…
cs.LG2026
Neonatal Hypoxic-ischaemic Encephalopathy Classification from the EEG and HRV Signals Using a Conformer based Masked Autoencoder
Shuwen Yu, William P Marnane, Geraldine B. Boylan +1
In this paper, we propose the MAEConformer, a novel self-supervised learning framework that combines the Conformer architecture with the Masked Autoencoder (MAE) paradigm for large…
cs.LG2026
HRVConformer: Neonatal Hypoxic-Ischemic Encephalopathy Classification from the Heart Rate signals
Shuwen Yu, William P Marnane, Geraldine B. Boylan +1
This paper presents the HRVConformer, a novel deep learning architecture for the classification of hypoxic-ischemic encephalopathy (HIE) using the instantaneous heart rate (HR) sig…