iXplain_CDS

Interoperable and eXplainable Clinical Decision Support

Group Lead

General aim

The junior research group iXplain_CDS aims to design, implement, and evaluate interoperable and explainable AI-based clinical decision support systems (CDSS) for a variety of medical use cases. Our overarching goal is to improve patient care by enabling robust, transparent, and reusable decision support across institutions. By leveraging routine clinical data — enriched with additional research data — we strive to generate dynamic, intelligent models that provide novel, personalized treatment strategies. Central to our mission are patient well-being, the traceability of recommendations, and the dissemination of innovative diagnostic and therapeutic procedures to a broader clinical audience.

Focus of research

Our research targets key challenges in medical informatics and clinical decision support:
• Integration of knowledge- and data-driven AI models to harness heterogeneous, high-dimensional clinical and non-clinical data.
• Cross-institutional applicability through the use of open international standards and seamless integration with clinical software landscape.
• Explainability and interpretability of recommendations including investigation of factors that influence comprehension to increase trust among clinicians and patients.
• Data modelling and interoperability to ensure sustainable reuse in different clinical contexts.
• Clinical evaluation of decision support systems in real-world environments and clinical trials.