The Analytics and Informatics for Child Health (AICH) group, led by Prof. Dr. Ece Özkan Elsen at the University of Basel and embedded in the Botnar Research Centre for Child Health (BRCCH), develops AI-driven healthcare solutions for pediatrics.

Children are not small adults. Their anatomy, physiology, and disease presentations differ from those of adults, yet most medical AI is built on adult data and transfers poorly to pediatric care. Clinical data for children is also scarcer, more heterogeneous, and spread across modalities that are rarely analyzed together. AICH works to close this gap.

Our research integrates multimodal data, including medical images, clinical records, and physiological signals, to learn representations that reflect how clinicians actually reason across evidence. We build models that are interpretable, bias-aware, and robust across age, sex, and clinical setting, so that their predictions can be trusted and acted on. The goal is to support precision diagnosis and treatment for children and adolescents, from early risk detection to individualized care.

We develop methods at the intersection of machine learning, representation learning, and clinical science, and we validate them on real pediatric cohorts in close collaboration with clinicians and partners. We care about methods that are not only accurate but also transparent and fair, because tools used in pediatric care must be accountable to the children, families, and clinicians who depend on them.