AI in Pedriatic CHD

We develop trustworthy AI solutions for pediatric cardiology in close collaboration with MHH to enable data-driven and personalized clinical decision support.

Group Lead

General aim

The aim of this junior research group is to develop and evaluate artificial intelligence–based methods for improving the diagnosis, prognosis, and clinical management of congenital heart diseases (CHD) in children. In close cooperation with the Department of Pediatric Cardiology at Hannover Medical School (MHH), we integrate AI technologies with echocardiography and clinical data to support reliable, explainable, and privacy-preserving clinical decision-making.

Focus of research

Our research focuses on AI-driven analysis of pediatric cardiac imaging and health data for individualized diagnostics and therapy. Key topics include automated disease classification and segmentation of cardiac structures in echocardiography, quantitative assessment of cardiac function, and the development of explainable and federated learning models to ensure transparency and data protection. In addition, we investigate the use of large language models to interpret clinical guidelines and patient records, and to support critical decisions such as the timing and planning of interventional procedures in complex congenital heart diseases.