4 papers
STAL: Spike Threshold Adaptive Learning Encoder for Classification of Pain-Related Biosignal Data
Freek Hens, Mohammad Mahdi Dehshibi, Leila Bagheriye +2
This paper presents the first application of spiking neural networks (SNNs) for the classification of chronic lower back pain (CLBP) using the EmoPain dataset. Our work has two mai…
Generative artificial intelligence in ophthalmology: multimodal retinal images for the diagnosis of Alzheimer's disease with convolutional neural networks
I. R. Slootweg, M. Thach, K. R. Curro-Tafili +7
Background/Aim. This study aims to predict Amyloid Positron Emission Tomography (AmyloidPET) status with multimodal retinal imaging and convolutional neural networks (CNNs) and to…
Neural Population Decoding and Imbalanced Multi-Omic Datasets For Cancer Subtype Diagnosis
Charles Theodore Kent, Leila Bagheriye, Johan Kwisthout
Recent strides in the field of neural computation has seen the adoption of Winner Take All (WTA) circuits to facilitate the unification of hierarchical Bayesian inference and spiki…
Bayesian Integration of Information Using Top-Down Modulated WTA Networks
Otto van der Himst, Leila Bagheriye, Johan Kwisthout
Winner Take All (WTA) circuits a type of Spiking Neural Networks (SNN) have been suggested as facilitating the brain's ability to process information in a Bayesian manner. Research…