In the presence of the President of the University of Ninevah, Prof. Dr. Osama Ismail Al-Mashhadani,
a master’s thesis was discussed at the College of Electronics Engineering, University of Ninevah, on Monday, April 7, 2025, by researcher Zeina Mahmoud Mousa, entitled:
“Deep Learning for Acute Lymphoblastic Leukemia Detection.”
The thesis focused on the potential of classifying Acute Lymphoblastic Leukemia (ALL) using machine learning and deep learning techniques.
The aim of the thesis was to propose lightweight and low-complexity models based on machine learning and deep learning with high accuracy for classifying ALL by relying on feature extraction.
The thesis concluded that feature extraction and parameter tuning significantly contribute to improving accuracy. Additionally, it found that non-complex datasets can be classified effectively using machine learning without the need for deep learning.
The discussion committee was chaired by Asst. Prof. Dr. Mohammed Hazem Al-Jammas, and included:
• Lecturer Dr. Majid Dhirar Younis from the College of Electronics Engineering, University of Ninevah
• Asst. Prof. Dr. Sinan Hossam Mahdi from the Ministry of Higher Education and Scientific Research
• Supervised by Asst. Prof. Dr. Mohammed Abdulmutalib Mohammed
We extend our best wishes for success and continued achievements to the researcher and the discussion committee.
