Master’s Thesis Defense on an Intelligent System for Skin Tumor Diagnosis Using Artificial Intelligence at the College of Medicine – Al-Nahrain University

The Department of Physiology and Medical Physics at the College of Medicine, Al-Nahrain University, discussed the Master’s thesis submitted by the student Hawraa Riyadh Hamza, entitled:

“Skin Tumor Diagnosis Using Deep Learning and Handcrafted Features”

The thesis focused on developing an automated system for classifying skin lesions into benign and malignant types using artificial intelligence techniques. The approach combined features extracted through deep learning with handcrafted features to enhance the accuracy of medical diagnosis.

The process began with pre-processing of skin images to improve their quality, followed by feature extraction using deep neural networks along with handcrafted characteristics that precisely describe tissue properties. These data were then input into four classification models, the most prominent being the Support Vector Machine (SVM) model, which achieved the highest accuracy of 97.1%. The evaluation was conducted by splitting the data into 80% for training and 20% for testing, reflecting the reliability of the results and the potential of the proposed system to support medical decision-making in the early detection of skin tumors.

The discussion committee consisted of:

• Asst. Prof. Dr. Mazin Kamel Hamed – Chair

• Asst. Prof. Dr. Ammar Mousa Jawad – Member

• Asst. Prof. Dr. Asaad Faleh Qasim – Member

• Prof. Dr. Hussein Saleh Hassan – Member and Supervisor

• Prof. Dr. Ali Majeed Hassan – Member and Supervisor

The student was awarded a grade of Excellent following a scientific discussion that highlighted the importance, precision, and impact of the research in the medical field.

Media and Government Communication Division
College of Medicine – Al-Nahrain University