We explore the dynamic landscape of “Medical Knowledge and Decision Support” by investigating the impacts and opportunities arising from digitalization in the clinic.

About us

The overarching objectives of the research of the Medical Knowledge and Decision Support group are to accelerate translation and integration of evidence into the clinic and to ensure that technological progress is aligned with the needs of clinicians.

Clinican Experiences, Interpretability and Trust

Our research focuses on understanding clinician experiences with digital tools and artificial intelligence, aiming to strategically guide future developments for greater clinical impact through enhanced interpretability of predictive models and qualitative exploration of trust and user experiences.

Artificial Intelligence

We investigate the use of advanced artificial intelligence to integrate prior knowledge with large-scale machine learning for informed predictions, including transfer learning for powerful applications in metabolism and physical activity, adaptable to diverse biomedical data types.

Evidence Synthesis
and Knowledge Management

We use machine learning and artificial intelligence to enhance evidence management, including discovery, extraction, synthesis, and translation of animal model research into prioritized human hypotheses. Our goal is to support partial automation of biomedical evidence synthesis, speeding up the translation of evidence into clinical implementation


School of Medicine
University of St.Gallen (HSG)
St. Jakob-Strasse 21
9000 St.Gallen, Switzerland

Institut for Implementation Science in Health Care (IfIS)
Universität Zürich
Universitätsstrasse 84
8006 Zürich, Switzerland