AIMID (Artificial Intelligence for Medical Imaging and Data) is an interdisciplinary research group that develops artificial intelligence-, machine learning-, and deep learning-based methods for the analysis of clinical data and medical images. Our research group brings together computer engineers, radiologists, and researchers from various healthcare disciplines to develop solutions for diagnosis, classification, segmentation, staging, prognosis prediction, and clinical decision support.

The main research areas of our group include the AI-assisted analysis of oncological diseases, particularly breast and prostate cancer. Our studies focus on classification, lesion segmentation, cancer staging, and risk assessment using breast magnetic resonance imaging (MRI), abbreviated breast MRI, mammography, and multiparametric prostate MRI. In addition, breast cancer recurrence prediction and the development of predictive models for coronary artery disease, diabetes, and other chronic diseases based on clinical data are among our research activities.

The methods developed within AIMID encompass image processing, computer vision, optimization algorithms, explainable artificial intelligence, multimodal data analysis, and clinical decision support systems. Our research combines medical images with clinical data, including electronic health records, laboratory findings, and demographic information, to develop accurate, reliable, and clinically applicable artificial intelligence solutions.

The primary goal of our research group is to support early diagnosis, improve clinical decision-making processes, and contribute to personalized medicine by integrating artificial intelligence technologies into healthcare in a reliable, ethical, and explainable manner. In line with this goal, conducting national and international research projects, strengthening interdisciplinary collaborations, and developing innovative solutions for healthcare are among our main priorities.