65 citations · 84 across the 9 of their papers we have counts for
10 papers
Explainable AI for Mental Health Emergency Returns: Integrating LLMs with Predictive Modeling
Abdulaziz Ahmed, Mohammad Saleem, Mohammed Alzeen +5
Importance: Emergency department (ED) returns for mental health conditions pose a major healthcare burden, with 24-27% of patients returning within 30 days. Traditional machine lea…
Reddit-Impacts: A Named Entity Recognition Dataset for Analyzing Clinical and Social Effects of Substance Use Derived from Social Media
Yao Ge, Sudeshna Das, Karen O'Connor +3
Substance use disorders (SUDs) are a growing concern globally, necessitating enhanced understanding of the problem and its trends through data-driven research. Social media are uni…
Evaluating Large Language Models for Health-Related Text Classification Tasks with Public Social Media Data
Yuting Guo, Anthony Ovadje, Mohammed Ali Al-Garadi +1
Large language models (LLMs) have demonstrated remarkable success in NLP tasks. However, there is a paucity of studies that attempt to evaluate their performances on social media-b…
Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems
Ayoub Si-ahmed, Mohammed Ali Al-Garadi, Narhimene Boustia
The Internet of Medical Things transcends traditional medical boundaries, enabling a transition from reactive treatment to proactive prevention. This innovative method revolutioniz…
Machine Learning Applications in Studying Mental Health Among Immigrants and Racial and Ethnic Minorities: A Systematic Review
Khushbu Khatri Park, Abdulaziz Ahmed, Mohammed Ali Al-Garadi
Background: The use of machine learning (ML) in mental health (MH) research is increasing, especially as new, more complex data types become available to analyze. By systematically…
Adopting the Multi-answer Questioning Task with an Auxiliary Metric for Extreme Multi-label Text Classification Utilizing the Label Hierarchy
Li Wang, Ying Wah Teh, Mohammed Ali Al-Garadi
Extreme multi-label text classification utilizes the label hierarchy to partition extreme labels into multiple label groups, turning the task into simple multi-group multi-label cl…
Few-shot learning for medical text: A systematic review
Yao Ge, Yuting Guo, Yuan-Chi Yang +2
Objective: Few-shot learning (FSL) methods require small numbers of labeled instances for training. As many medical topics have limited annotated textual data in practical settings…
Survey of Machine Learning Based Intrusion Detection Methods for Internet of Medical Things
Ayoub Si-Ahmed, Mohammed Ali Al-Garadi, Narhimene Boustia
The Internet of Medical Things (IoMT) has revolutionized the healthcare industry by enabling physiological data collection using sensors, which are transmitted to remote servers fo…
Design Challenges of Multi-UAV Systems in Cyber-Physical Applications: A Comprehensive Survey, and Future Directions
Reza Shakeri, Mohammed Ali Al-Garadi, Ahmed Badawy +5
Unmanned Aerial Vehicles (UAVs) have recently rapidly grown to facilitate a wide range of innovative applications that can fundamentally change the way cyber-physical systems (CPSs…
A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
Mohammed Ali Al-Garadi, Amr Mohamed, Abdulla Al-Ali +2
The Internet of Things (IoT) integrates billions of smart devices that can communicate with one another with minimal human intervention. It is one of the fastest developing fields…