Explanipedia

Leveraging K-Means Clustering and Z-Score for Anomaly Detection in Bitcoin Transactions Open

J. R. Patel, Joseph Reiner, Brenden Stilwell, Abdullah Wahbeh, Raed Seetan · 2025

With the growing popularity of cryptocurrencies, detecting potential market manipulation and fraudulent activities has become crucial for maintaining market integrity. In this study, we aim to detect anomalous Bitcoin transactions using an…

Predictive Analytics for Thyroid Cancer Recurrence: A Machine Learning Approach Open

Elizabeth A. Clark, Samantha A. Price, Theresa Lucena, Bailey Haberlein, Abdullah Wahbeh , et al. · 2024

Differentiated thyroid cancer (DTC), comprising papillary and follicular thyroid cancers, is the most prevalent type of thyroid malignancy. Accurate prediction of DTC is crucial for improving patient outcomes. Machine learning (ML) offers …

Predictive Analytics for Thyroid Cancer Recurrence: A Machine Learning Approach Open

Elizabeth A. Clark, Samantha A. Price, Theresa Lucena, Bailey Haberlein, Abdullah Wahbeh , et al. · 2024

Differentiated thyroid cancer (DTC), comprising of papillary and follicular thyroid cancers, is the most prevalent type of thyroid malignancy. Accurate prediction of DTC is crucial for improving patient outcomes. Machine learning (ML) offe…

Health Benefits and Adverse Effects of Kratom: A Social Media Text-Mining Approach Open

Abdullah Wahbeh, Mohammad Al-Ramahi, Omar El-Gayar, Tareq Nasralah, Ahmed Elnoshokaty · 2024

Background: Kratom is a substance that alters one’s mental state and is used for pain relief, mood enhancement, and opioid withdrawal, despite potential health risks. In this study, we aim to analyze the social media discourse about kratom…

Predicting Question Quality on StackOverflow with Neural Networks Open

Mohammad Al-Ramahi, Izzat Alsmadi, Abdullah Wahbeh · 2024

The wealth of information available through the Internet and social media is unprecedented. Within computing fields, websites such as Stack Overflow are considered important sources for users seeking solutions to their computing and progra…

Energy Efficiency of Training Neural Network Architectures: An Empirical Study Open

Omar El-Gayar, PingSun Leung, Abdullah Wahbeh, Arno Scharl · 2023

The evaluation of Deep Learning (DL) models has traditionally focused on criteria such as accuracy, F1 score, and related measures. The increasing availability of high computational power environments allows the creation of deeper and more…

A comparative analysis of anti-vax discourse on twitter before and after COVID-19 onset Open

Tareq Nasralah, Ahmed Elnoshokaty, Omar El-Gayar, Mohammad Al-Ramahi, Abdullah Wahbeh · 2022

This study aimed to identify and assess the prevalence of vaccine-hesitancy-related topics on Twitter in the periods before and after the Coronavirus Disease 2019 (COVID-19) outbreak. Using a search query, 272,780 tweets associated with an…

Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data Open

Mohammad Al-Ramahi, Ahmed Elnoshokaty, Omar El-Gayar, Tareq Nasralah, Abdullah Wahbeh · 2021

Background Despite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media. Objective This study aimed to investigate …

Adverse Health Effects of Kratom: An Analysis of Social Media Data Open

Abdullah Wahbeh, Tareq Nasralah, Omar El-Gayar, Mohammad Al-Ramahi, Ahmed Elnoshokaty · 2021

This study investigates the adverse healthcare effects associated with the use of kratom. Using machine learning techniques, we analyzed a total of 36,516 users’ posts related to kratom. The results and analysis showed that social media co…

Mental health and the COVID-19 pandemic: Analysis of twitter discourse Open

Omar El-Gayar, Abdullah Wahbeh, Tareq Nasralah, Ahmed Elnoshokaty, Mohammad Al-Ramahi · 2021

This study analyzed Twitter discourse to understand the association of the COVID-19 pandemic with mental health. The study compared tweets’ volume over time, tweets’ volume per mental health category, emotions, and the top hashtags on ment…

Dark Web Analytics : A Comparative Study of Feature Selection and Prediction Algorithms Open

Andrew Allhusen, Izzat Alsmadi, Abdullah Wahbeh, Mohammad Al-Ramahi, Ahmad Al-Omari · 2021

Public Discourse Against Masks in the COVID-19 Era: Infodemiology Study of Twitter Data (Preprint) Open

Mohammad Al-Ramahi, Ahmed Elnoshokaty, Omar El-Gayar, Tareq Nasralah, Abdullah Wahbeh · 2020

BACKGROUND Despite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media. OBJECTIVE This study aimed to investiga…

Mining Physicians’ Opinions on Social Media to Obtain Insights Into COVID-19: Mixed Methods Analysis Open

Abdullah Wahbeh, Tareq Nasralah, Mohammad Al-Ramahi, Omar El-Gayar · 2020

Background The coronavirus disease (COVID-19) pandemic is considered to be the most daunting public health challenge in decades. With no effective treatments and with time needed to develop a vaccine, alternative approaches are being used …

Health Risks of e-cigarettes: Analysis of Twitter Data Using Topic Mining. Open

Abdullah Wahbeh, Mohammad Al-Ramahi, Omar El-Gayar, Tareq Nasralah · 2020

The recent rise of e-cigarettes and vaping products has increased concerns that another young generation may become addicted to nicotine. Recently, it becomes evident that several health issues are related to the use of e-cigarettes and va…

Robots, Artificial Intelligence, and Service Automation in Travel, Tourism and Hospitality Open

Dimitrios Buhalis, Juho Pesonen, Μαριάννα Σιγάλα, Rob Law, Stanislav Ivanov , et al. · 2019

Using a combination of theoretical discussion and real-world case studies, this book analyses the use of robotics, artificial intelligence and services automation (RAISA) within the travel, tourism and hospitality industries. Divided into …

Patients’ Characteristics Effecting the Use of a MyChart Patient Portal Open

Ali Ahmed, Tareq Nasralah, Abdullah Wahbeh, Cherie Noteboom · 2019

In this study, we have studied the effects of patients’ characteristics on the use of an online patient portal. We have created an explanatory model to illustrate the relationship between the patient-portal use and the patients’ demographi…

Discovering Patient Portal Features Critical to User Satisfaction: A Systematic Analysis Open

Abdullah Wahbeh, Mohammad Al-Ramahi, Cherie Noteboom, Tareq Nasralah · 2019

Patient portals are consumer-centric tools that can strengthen consumers’ ability to actively manage their own health and healthcare. The incorporation of patient portals provides the promise to deliver quality, low costs services to the p…

Online Health Recommendation System: A Social Support Perspective Open

Tareq Nasralah, Cherie Noteboom, Abdullah Wahbeh, Mohammad Al-Ramahi · 2017

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