338 citations
- Al Madinah International UniversityMY3 papers
- École de Technologie SupérieureCA3 papers
- Guilin University of Electronic TechnologyCN3 papers
- University of Technology MalaysiaMY3 papers
- Jadara UniversityJO2 papers
- National Guard Health AffairsSA2 papers
- National Research Institute of Astronomy and GeophysicsEG2 papers
- Nihon UniversityJP2 papers
- Petra UniversityJO2 papers
- Prince Mohammed bin Abdulaziz HospitalSA2 papers
- University of JeddahSA2 papers
- Zarqa UniversityJO2 papers
6 papers · 1 filter
Enhanced Arabic-language cyberbullying detection: deep embedding and transformer (BERT) approaches
Ebtesam Jaber Aljohani, Wael M. S. Yafoo
Recent technological advances in smartphones and communications, including the growth of such online platforms as massive social media networks such as X (formerly known as Twitter…
Towards a Transparent and Interpretable AI Model for Medical Image Classifications
Binbin Wen, Yihang Wu, Tareef Daqqaq +1
The integration of artificial intelligence (AI) into medicine is remarkable, offering advanced diagnostic and therapeutic possibilities. However, the inherent opacity of complex AI…
Enhancing Dual Network Based Semi-Supervised Medical Image Segmentation with Uncertainty-Guided Pseudo-Labeling
Yunyao Lu, Yihang Wu, Ahmad Chaddad +2
Despite the remarkable performance of supervised medical image segmentation models, relying on a large amount of labeled data is impractical in real-world situations. Semi-supervis…
Domain Adaptation Techniques for Natural and Medical Image Classification
Ahmad Chaddad, Yihang Wu, Reem Kateb +1
Domain adaptation (DA) techniques have the potential in machine learning to alleviate distribution differences between training and test sets by leveraging information from source…
Machine Learning-Based Quantification of Vesicoureteral Reflux with Enhancing Accuracy and Efficiency
Muhyeeddin Alqaraleh, Mowafaq Salem Alzboon, Mohammad Subhi Al-Batah +4
Vesicoureteral reflux (VUR) is traditionally assessed using subjective grading systems, which introduces variability in diagnosis. This study investigates the use of machine learni…
Classifying Dental Care Providers Through Machine Learning with Features Ranking
Mohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Muhyeeddin Alqaraleh +2
This study investigates the application of machine learning (ML) models for classifying dental providers into two categories - standard rendering providers and safety net clinic (S…