Digital health in primordial and primary stroke prevention: a systematic review

VL Feigin, M Owolabi, GJ Hankey, J Pandian… - Stroke, 2022 - Am Heart Assoc
The stroke burden continues to grow across the globe, disproportionally affecting
developing countries. This burden cannot be effectively halted and reversed without …

Spiking neural networks: background, recent development and the NeuCube architecture

C Tan, M Šarlija, N Kasabov - Neural Processing Letters, 2020 - Springer
This paper reviews recent developments in the still-off-the-mainstream information and data
processing area of spiking neural networks (SNN)—the third generation of artificial neural …

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications

N Kasabov, NM Scott, E Tu, S Marks, N Sengupta… - Neural Networks, 2016 - Elsevier
The paper describes a new type of evolving connectionist systems (ECOS) called evolving
spatio-temporal data machines based on neuromorphic, brain-like information processing …

Stroke lesion segmentation and deep learning: a comprehensive review

M Malik, B Chong, J Fernandez, V Shim, NK Kasabov… - Bioengineering, 2024 - mdpi.com
Stroke is a medical condition that affects around 15 million people annually. Patients and
their families can face severe financial and emotional challenges as it can cause motor …

Personalized spiking neural network models of clinical and environmental factors to predict stroke

M Doborjeh, Z Doborjeh, A Merkin… - Cognitive …, 2022 - Springer
The high incidence of stroke occurrence necessitates the understanding of its causes and
possible ways for early prediction and prevention. In this respect, statistical methods offer the …

Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on …

E Capecci, N Kasabov, GY Wang - Neural Networks, 2015 - Elsevier
The paper presents a methodology for the analysis of functional changes in brain activity
across different conditions and different groups of subjects. This analysis is based on the …

[PDF][PDF] Evolving spiking neural networks methods for classification problem: a case study in flood events risk assessment

MHA Abdullah, M Othman, S Kasim… - … Journal of Electrical …, 2019 - pdfs.semanticscholar.org
Analysing environmental events such as predicting the risk of flood is considered as a
challenging task due to the dynamic behaviour of the data. One way to correctly predict the …

A spiking neural networks model with fuzzy-weighted K-nearest neighbour classifier for real-world flood risk assessment

MHA Abdullah, M Othman, S Kasim… - … Conference on Soft …, 2019 - Springer
Inspired by the brain working mechanism, the spiking neural networks has proven the
capability of revealing significant association between different variables spike behavior …

Ischemic stroke prediction by exploring sleep related features

J Xie, Z Wang, Z Yu, B Guo, X Zhou - Applied Sciences, 2021 - mdpi.com
Ischemic stroke is one of the typical chronic diseases caused by the degeneration of the
neural system, which usually leads to great damages to human beings and reduces life …

Empowering self-management through m-health applications

M Othman, NM Halil, MM Yusof… - MATEC Web of …, 2018 - matec-conferences.org
The advancement in mobile technology has led towards a new frontier of medical
intervention that never been thought possible before. Through the development of MedsBox …