Hany Alashwal
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View article: Enhancing Diagnostic Accuracy by Bypassing Traditional Imputation and Leveraging Missing Data in Alzheimer's Disease Detection Models
Enhancing Diagnostic Accuracy by Bypassing Traditional Imputation and Leveraging Missing Data in Alzheimer's Disease Detection Models Open
Researchers often encounter significant hurdles when dealing with datasets that contain a vast number of missing values. This predicament forces them to make a tough choice: either discard a substantial amount of data, which could drastica…
View article: Generative AI and large language models: A new frontier in reverse vaccinology
Generative AI and large language models: A new frontier in reverse vaccinology Open
Reverse vaccinology is an emerging concept in the field of vaccine development as it facilitates the identification of potential vaccine candidates. Biomedical research has been revolutionized with the recent innovations in Generative Arti…
View article: A neural network model of mathematics anxiety: The role of attention
A neural network model of mathematics anxiety: The role of attention Open
Anxiety about performing numerical calculations is becoming an increasingly important issue. Termed mathematics anxiety , this condition negatively impacts performance in numerical tasks which can affect education outcomes and future emplo…
View article: A Neurocomputational Analysis Review of Dorsolateral Prefrontal Cortex rTMS Treatments of Neurological Disorder
A Neurocomputational Analysis Review of Dorsolateral Prefrontal Cortex rTMS Treatments of Neurological Disorder Open
Repetitive transcranial magnetic stimulation (rTMS) to the dorsolateral prefrontal cortex (DLPFC) has been used as a treatment for several psychiatric and neurological disorders, including depression, bipolar disorder, anxiety, eating diso…
View article: SEBD: A Stream Evolving Bot Detection Framework with Application of PAC Learning Approach to Maintain Accuracy and Confidence Levels
SEBD: A Stream Evolving Bot Detection Framework with Application of PAC Learning Approach to Maintain Accuracy and Confidence Levels Open
A simple supervised learning model can predict a class from trained data based on the previous learning process. Trust in such a model can be gained through evaluation measures that ensure fewer misclassification errors in prediction resul…
View article: Bot-MGAT: A Transfer Learning Model Based on a Multi-View Graph Attention Network to Detect Social Bots
Bot-MGAT: A Transfer Learning Model Based on a Multi-View Graph Attention Network to Detect Social Bots Open
Twitter, as a popular social network, has been targeted by different bot attacks. Detecting social bots is a challenging task, due to their evolving capacity to avoid detection. Extensive research efforts have proposed different techniques…
View article: Prediction of Site Directed miRNAs as Key Players of Transcriptional Regulators Against Influenza C Virus Infection Through Computational Approaches
Prediction of Site Directed miRNAs as Key Players of Transcriptional Regulators Against Influenza C Virus Infection Through Computational Approaches Open
MicroRNAs (miRNAs) are small non-coding RNAs that play critical roles in gene expression, cell differentiation, and immunity against viral infections. In this study, we have used the computational tools, RNA22, RNAhybrid, and miRanda, to p…
View article: Applications of machine learning to behavioral sciences: focus on categorical data
Applications of machine learning to behavioral sciences: focus on categorical data Open
In the last two decades, advancements in artificial intelligence and data science have attracted researchers' attention to machine learning. Growing interests in applying machine learning algorithms can be observed in different scientific …
View article: A Synaptic Pruning-Based Spiking Neural Network for Hand-Written Digits Classification
A Synaptic Pruning-Based Spiking Neural Network for Hand-Written Digits Classification Open
A spiking neural network model inspired by synaptic pruning is developed and trained to extract features of hand-written digits. The network is composed of three spiking neural layers and one output neuron whose firing rate is used for cla…
View article: Neural Substrates of the Drift-Diffusion Model in Brain Disorders
Neural Substrates of the Drift-Diffusion Model in Brain Disorders Open
Many studies on the drift-diffusion model (DDM) explain decision-making based on a unified analysis of both accuracy and response times. This review provides an in-depth account of the recent advances in DDM research which ground different…
View article: Vaccine versus Variants (3Vs): Are the COVID-19 Vaccines Effective against the Variants? A Systematic Review
Vaccine versus Variants (3Vs): Are the COVID-19 Vaccines Effective against the Variants? A Systematic Review Open
Background: With the emergence and spread of new SARS-CoV-2 variants, concerns are raised about the effectiveness of the existing vaccines to protect against these new variants. Although many vaccines were found to be highly effective agai…
View article: Hybrid feature selection approach to identify optimal features of profile metadata to detect social bots in Twitter
Hybrid feature selection approach to identify optimal features of profile metadata to detect social bots in Twitter Open
The last few years have revealed that social bots in social networks have become more sophisticated in design as they adapt their features to avoid detection systems. The deceptive nature of bots to mimic human users is due to the advancem…
View article: A Systematic Literature Review of Student’ Performance Prediction Using Machine Learning Techniques
A Systematic Literature Review of Student’ Performance Prediction Using Machine Learning Techniques Open
Educational Data Mining plays a critical role in advancing the learning environment by contributing state-of-the-art methods, techniques, and applications. The recent development provides valuable tools for understanding the student learni…
View article: Explainable Feature Extraction Using a Neural Network with non-Synaptic Memory for Hand-Written Digit Classification
Explainable Feature Extraction Using a Neural Network with non-Synaptic Memory for Hand-Written Digit Classification Open
The human brain recognizes hand-written digits by extracting the features from a few training samples that compose the digit image including horizontal, vertical, and orthogonal lines as well as full or semi-circles. In this study, we pres…
View article: Latent Class and Transition Analysis of Alzheimer's Disease Data
Latent Class and Transition Analysis of Alzheimer's Disease Data Open
This study uses independent latent class analysis (LCA) and latent transition analysis (LTA) to explore accurate diagnosis and disease status change of a big Alzheimer's disease Neuroimaging Initiative (ADNI) data of 2,132 individuals over…
View article: Association of hypertension, diabetes, stroke, cancer, kidney disease, and high-cholesterol with COVID-19 disease severity and fatality: a systematic review
Association of hypertension, diabetes, stroke, cancer, kidney disease, and high-cholesterol with COVID-19 disease severity and fatality: a systematic review Open
Objective To undertake a review and critical appraisal of published/preprint reports that offer methods of determining the effects of hypertension, diabetes, stroke, cancer, kidney issues, and high-cholesterol on COVID-19 disease severity.…
View article: The Application of Unsupervised Clustering Methods to Alzheimer’s Disease
The Application of Unsupervised Clustering Methods to Alzheimer’s Disease Open
Clustering is a powerful machine learning tool for detecting structures in datasets. In the medical field, clustering has been proven to be a powerful tool for discovering patterns and structure in labeled and unlabeled datasets. Unlike su…
View article: Data stream mining techniques: a review
Data stream mining techniques: a review Open
A plethora of infinite data is generated from the Internet and other information sources. Analyzing this massive data in real-time and extracting valuable knowledge using different mining applications platforms have been an area for resear…
View article: Applying Big Data Methods to Understanding Human Behavior and Health
Applying Big Data Methods to Understanding Human Behavior and Health Open
OPINION article Front. Comput. Neurosci., 16 October 2018 | https://doi.org/10.3389/fncom.2018.00084
View article: Molecular Docking and Dynamic Simulation of AZD3293 and Solanezumab Effects Against BACE1 to Treat Alzheimer's Disease
Molecular Docking and Dynamic Simulation of AZD3293 and Solanezumab Effects Against BACE1 to Treat Alzheimer's Disease Open
The design of novel inhibitors to target BACE1 with reduced cytotoxicity effects is a promising approach to treat Alzheimer's disease (AD). Multiple clinical drugs and antibodies such as AZD3293 and Solanezumab are being tested to investig…