The Department of Intelligent Medical Systems at the College of Biomedical Informatics discussed the graduation projects of fourth-year students, supervised by Lecturer Zainab Mustafa, instructor of Medical Data Mining. The students presented a range of applied projects addressing highly important medical topics.

The projects explored the use of data mining and artificial intelligence techniques to predict chronic diseases and analyze health risks, aligning with the actual needs of the healthcare sector and contributing to keeping pace with the latest developments in the field of medical artificial intelligence.

The projects covered various areas, including predicting diabetes and heart disease, classifying stages of hypertension, analyzing obesity risks, detecting anemia based on laboratory test data, diagnosing breast cancer, and analyzing the comorbidity between diabetes and hypertension.

The project titles included the following:

• Diabetes Risk Prediction

• Hypertension Stage Classification

• Obesity Risk Analysis

• Heart Disease Prediction

• Anemia Detection Using Laboratory Test Data

• Breast Cancer Diagnosis

• Comorbidity Analysis of Diabetes and Hypertension

This achievement reflects the students’ high level of competence and their ability to apply theoretical knowledge to practical medical applications that serve the healthcare sector. It also demonstrates the college’s commitment to supporting applied projects and enhancing the role of smart medical systems in serving the healthcare sector.