On Thursday, May 15, 2025, a master’s thesis titled “Coronavirus Lung Disease Recognition Using Machine Learning Techniques” was defended at the University of Nineveh, College of Electronic Engineering, Department of Electronics Engineering, by student Raghad Waleed Mohammed.
The thesis investigated the use of machine learning techniques (deep learning algorithms and Raspberry Pi) to diagnose COVID-19-induced pulmonary obstruction, aiming to provide an early detection tool for severe pneumonia using chest X-ray images. This research offers a cost-effective diagnostic solution for healthcare support systems.
-:Thesis Committee Members
Prof. Dr. Shifa Abdulrahman Dawood – University of Mosul, College of Engineering (Chair)
Assist. Prof. Dr. Sahar Lazim Qadouri – University of Nineveh, College of Electronic Engineering (Member)
Dr. Azhar Sabah Abdulaziz – University of Nineveh, College of Information Technology (Member)
Prof. Dr. Khaled Khalil Mohammed – University of Nineveh, College of Electronic Engineering (Member & Supervisor)
**Assist. Prof. Dr. Omar Ibrahim Ahmed **– Northern Technical University, College of Engineering for Computer Science and Artificial Intelligence (Member & Supervisor)
We extend our congratulations to the researcher and the committee, wishing them continued success and achievement
