Ivana Išgum

Ivana Išgum is a Full Professor in AI for Medical Image Analysis at the University of Amsterdam, with appointments at the Amsterdam University Medical Center (Biomedical Engineering and Physics, Radiology and Nuclear Medicine) and the Faculty of Medicine (Informatics Institute). She leads the interfaculty research group Quantitative Healthcare Analysis (qurAI), bridging the Faculties of Medicine and Science. Her work integrates machine learning and deep learning to enhance clinical decision-making in radiology and cardiology.

Her research interests include:

• Quantitative medical image analysis
• Coronary artery disease detection and prognosis
• Neonatal brain development quantification
• Real-time AI for intravascular imaging
• Cardiac arrhythmia prediction

The 15 most recent publications highlight trends in cardiovascular risk stratification using multimodal data, advanced deep learning for coronary OCT/CT segmentation, and AI applications in fetal/abdominal imaging. Her work emphasizes trustworthy AI systems, image registration techniques, and multimodal data harmonization.

She leads ongoing projects in AI for:

• Cardiovascular risk in breast cancer survivors
• Coronary artery analysis in high-end CCTA
• PAD progression prediction
• Dilated cardiomyopathy diagnosis
• Real-time intravascular OCT characterization

Her lab (qurAI) focuses on clinical AI implementation, addressing challenges in data variability and real-time processing.