[HTML][HTML] A comparative analysis of meta-heuristic optimization algorithms for feature selection on ML-based classification of heart-related diseases

Ş Ay, E Ekinci, Z Garip - The Journal of Supercomputing, 2023 - Springer
This study aims to use a machine learning (ML)-based enhanced diagnosis and survival
model to predict heart disease and survival in heart failure by combining the cuckoo search …

A comparative study of machine learning models for cyber-attacks detection in wireless sensor networks

S Ismail, TT Khoei, R Marsh… - 2021 IEEE 12th Annual …, 2021 - ieeexplore.ieee.org
Wireless Sensor Network is a key technology for Internet of Things, but it is an example of
energy-restricted networks. In such networks with a large number of deployed sensors with …

Deep Learning for Alzheimer's Disease Prediction: A Comprehensive Review

I Malik, A Iqbal, YH Gu, MA Al-antari - Diagnostics, 2024 - mdpi.com
Alzheimer's disease (AD) is a neurological disorder that significantly impairs cognitive
function, leading to memory loss and eventually death. AD progresses through three stages …

Boosting-based models with tree-structured parzen estimator optimization to detect intrusion attacks on smart grid

TT Khoei, S Ismail, N Kaabouch - 2021 IEEE 12th Annual …, 2021 - ieeexplore.ieee.org
Smart grid is an emerging technology that transfers power to users intelligently through two-
way communication. Despite the benefits of this network, it is prone to different cyber-attacks …

Residual convolutional network for detecting attacks on intrusion detection systems in smart grid

TT Khoei, WC Hu, N Kaabouch - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Smart grid provides several benefits, such as reliability and affordability. Despite its benefits,
this network has several shortcomings, including a lack of security. DoS attacks are …

Predicting Huntington's disease state with ensemble learning & sMRI: more than just the striatum

M Kohli, D Pustina, JH Warner, DC Alexander… - medRxiv, 2023 - medrxiv.org
Developing effective treatments for Huntington's disease (HD) requires reliable markers of
disease progression. Striatal atrophy has been the hallmark of HD progression, but …

[HTML][HTML] A polygenic stacking classifier revealed the complicated platelet transcriptomic landscape of adult immune thrombocytopenia

C Xu, R Zhang, M Duan, Y Zhou, J Bao, H Lu… - … Therapy-Nucleic Acids, 2022 - cell.com
Immune thrombocytopenia (ITP) is an autoimmune disease with the typical symptom of a low
platelet count in blood. ITP demonstrated age and sex biases in both occurrences and …

A Deep Learning Multi-Task Approach for the Detection of Alzheimer's Disease in a Longitudinal Study

TT Khoei, MA Ahajjam, WC Hu… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Alzheimer's Disease (AD) is one of the most common illnesses in the world, affecting
approximately fifty million people. In the United States, AD is the sixth leading cause of …

[图书][B] Evolutionary Intelligence for Healthcare Applications

TA Kumar, R Rajmohan, M Pavithra, S Balamurugan - 2022 - api.taylorfrancis.com
This book highlights various evolutionary algorithm techniques for various medical
conditions and introduces medical applications of evolutionary computation for real-time …

Investigation of Multi-dimensional Tensor Multi-task Learning for Modeling Alzheimer's Disease Progression

Y Zhang - 2024 - etheses.whiterose.ac.uk
Machine learning (ML) techniques for predicting Alzheimer's disease (AD) progression can
significantly assist clinicians and researchers in constructing effective AD prevention and …