Master’s thesis in the Department of Computer Science discusses an ECG recognition and annotation system based on deep learning technology

Under the auspices of the Head of the Department of Computer Science, Prof. Dr. Alaa Kazem Farhan, and in the presence of the scientific assistant, Assistant Professor Dr. Mustafa Jassim, and the administrative assistant, Assistant Professor Dr. Bashar Saadoun Mahdi, professors and students of the department, and within the program, the Department of Computer Science discussed the master’s thesis entitled Electrocardiograph Recognition and Explanation System Based on Deep Learning Technique

For the master’s student Mai Sadeq Khurshid Computer Science / General. On Sunday 8/12/2024 at the hall of the late Dr. Imad Kazem. The thesis aims to develop a system that combines high diagnostic accuracy and explainability of ECG through deep learning. This thesis developed an ECG recognition and interpretation system using a customized CNN model and Grad-CAM which achieves high accuracy and interpretability classification. The discussion committee consisted of Dr. Muthail Emaduddin Abdel-Moneim as chairman and members Farah Qais Abdullah, Dr. Khalil Ibrahim Gathwan, and Dr. Abdul Amir Abdullah Karim as a member and supervisor.