As part of the ongoing graduation project defenses for the AI and Data Science program (2025–2026), and in the presence of Prof. Dr. Wael Al-Aghbari, President of the University, and Prof. Dr. Sadiq Manna, Vice President for Academic Affairs, IUTT presented a distinguished research project titled: Adaptive MedFusionNet Framework for Skin Dataset.
The project aims to develop an intelligent framework for high-precision dermatological diagnosis. The team developed an innovative hybrid model, MedFusionNet, combining ConvNeXt and Vision Transformer architectures, achieving a classification accuracy of 94.58% across four major categories: cancerous, inflammatory, fungal, and bacterial diseases.
The system integrates Grad-CAM technology to provide heatmaps explaining the model’s focus within images, enhancing transparency and supporting reliable medical decision-making. This project embodies the university’s commitment to bridging scientific research with practical applications in the healthcare sector.
Team Members: Nada Al-Qumari, Wejdan Al-Samawi, Najla Al-Shahari.
Supervision: Prof. Dr. Fadhl Ba-Alawi.
Internal Defense Committee: Dr. Hamzah Jamel, Dr. Amin Shayae, Dr. Ayman Al-Sabri, Prof. Dr. Fadhl Ba-Alawi.
External Defense Committee: Prof. Dr. Ahmed Sultan Al-Hajami, Assoc. Prof. Dr. Malik Al-Jabri.
