Alaa Adham

Student Information

• Name: Alaa Adham
• Level: MSc
• University: University of Kurdistan Hewlêr
• Subject: Computer Science
• Research Area: Medical Data Analysis and Computational Medicine
• Status: Completed
• Supervisor: Dr. Polla Fattah
• Duration: 2023 - 2024

Research Focus

Alaa’s research focused on medical data analysis and computational medicine, including age and gender estimation from skeletal radiographs using deep learning. The work involved developing multi-factor classification systems for medical imaging.

Key Research Areas

Medical Imaging Analysis

• Age and gender estimation from skeletal radiographs
• Multi-factor classification using deep learning for X-ray images
• Medical image processing and analysis

Deep Learning Applications

• Implementing deep learning models for medical data analysis
• Developing classification systems for medical imaging
• Creating predictive models for medical diagnosis

Computational Medicine

• Processing and analyzing medical datasets
• Developing tools for medical decision support
• Creating frameworks for medical data analysis

Research Outcomes

• Successfully completed comprehensive medical data analysis
• Developed deep learning models for medical imaging
• Contributed to computational medicine research
• Completed thesis on medical data analysis methodologies

Technologies and Methodologies

• Deep learning frameworks
• Medical image processing
• Statistical analysis tools
• Classification algorithms
• Medical data visualization
• Computational medicine techniques

Impact

Alaa’s work has contributed to the advancement of computational medicine, providing tools for medical diagnosis and supporting healthcare decision-making processes.

Publications and Presentations

• Age and Gender Estimation from Skeletal Radiographs Using Deep Learning (2024) - Journal Article
• Multi-Factor Classification Using Deep Learning for X-ray Images (2024) - Journal Article
• Completed comprehensive thesis on medical data analysis
• Developed deep learning frameworks for medical imaging
• Contributed to computational medicine research

Academic Achievement

• Successfully completed MSc degree
• Developed expertise in medical data analysis
• Contributed to computational medicine research
• Thesis focused on practical applications of deep learning in medical imaging