4 papers
Learning Alzheimer's Disease Signatures by bridging EEG with Spiking Neural Networks and Biophysical Simulations
Szymon MamoÅ, Max Talanov, Alessandro Crimi
As the prevalence of Alzheimer's disease (AD) rises, improving mechanistic insight from non-invasive biomarkers is increasingly critical. Recent work suggests that circuit-level br…
SharpXR: Structure-Aware Denoising for Pediatric Chest X-Rays
Ilerioluwakiiye Abolade, Emmanuel Idoko, Solomon Odelola +6
Pediatric chest X-ray imaging is essential for early diagnosis, particularly in low-resource settings where advanced imaging modalities are often inaccessible. Low-dose protocols r…
Graph Attention Networks for Detecting Epilepsy from EEG Signals Using Accessible Hardware in Low-Resource Settings
Szymon Mazurek, Stephen Moore, Alessandro Crimi
Goal: Epilepsy remains under-diagnosed in low-income countries due to scarce neurologists and costly diagnostic tools. We propose a graph-based deep learning framework to detect ep…
End-to-end Stroke imaging analysis, using reservoir computing-based effective connectivity, and interpretable Artificial intelligence
Wojciech Ciezobka, Joan Falco-Roget, Cemal Koba +1
In this paper, we propose a reservoir computing-based and directed graph analysis pipeline. The goal of this pipeline is to define an efficient brain representation for connectivit…