7 citations · 14 across the 8 of their papers we have counts for
8 papers
Explaining Unsupervised Disease Staging in Huntington's Disease: Insights into Model Representations and Clusters
Lubna Mahmoud Abu Zohair, Hind Zantout
Huntington's disease (HD) is a progressive neurodegenerative disorder that affects motor, cognitive, and behavioral functions, where accurate characterization of disease progressio…
A Machine Learning-Based Framework for Discovering Huntington's Disease Stages: Integrating Graph Representation Learning and clustering to Uncover Progression Dynamics in Longitudinal Enroll-HD Dataset
Lubna M. Abu Zohair, Marta Vallejo, MD Azher Uddin +2
Huntington's disease (HD) is a progressive brain disorder that gradually affects movement, cognitive function, and behavior. Identifying the stage of the disease accurately and con…
Fine-Tuning Models for Automated Code Review Feedback
Smitha S Kumar, Michael A Lones, Manuel Maarek +1
Large Language Models have introduced new possibilities for programming education through personalized support, content creation, and automated feedback. While recent studies have…
Navigating Pitfalls: Evaluating LLMs in Machine Learning Programming Education
Smitha Kumar, Michael A. Lones, Manuel Maarek +1
The rapid advancement of Large Language Models (LLMs) has opened new avenues in education. This study examines the use of LLMs in supporting learning in machine learning education;…
Self-Supervised Learning for Pre-training Capsule Networks: Overcoming Medical Imaging Dataset Challenges
Heba El-Shimy, Hind Zantout, Michael A. Lones +1
Deep learning techniques are increasingly being adopted in diagnostic medical imaging. However, the limited availability of high-quality, large-scale medical datasets presents a si…
ActDroid: An active learning framework for Android malware detection
Ali Muzaffar, Hani Ragab Hassen, Hind Zantout +1
The growing popularity of Android requires malware detection systems that can keep up with the pace of new software being released. According to a recent study, a new piece of malw…
DroidDissector: A Static and Dynamic Analysis Tool for Android Malware Detection
Ali Muzaffar, Hani Ragab Hassen, Hind Zantout +1
DroidDissector is an extraction tool for both static and dynamic features. The aim is to provide Android malware researchers and analysts with an integrated tool that can extract a…
Reassessing feature-based Android malware detection in a contemporary context
Ali Muzaffar, Hani Ragab Hassen, Hind Zantout +1
We report the findings of a reimplementation of 18 foundational studies in feature-based machine learning for Android malware detection, published during the period 2013-2023. Thes…