Medical Knowledge and Decision Support

We advance “Medical Knowledge and Decision Support” with data science and artificial intelligence, and qualitatively explore digital transformation in the clinic.

The overarching objectives of the research of the Medical Knowledge and Decision Support group are to implement innovative data science approaches, accelerate discovery, translation and integration of evidence into clinics, and to align technological progress with the needs of clinicians.

Methods

Our research draws methodologically from data science, bioinformatics, computer science, and psychology. We build ontologies and an associated ecosystem for logic-based automation. We apply and develop predictive models using AI/ML, particularly LLMs and neuro-symbolic approaches. We apply mathematical approaches including constraint-based modelling. In addition, we use qualitative approaches to study human perspectives.

Use cases

Use Cases

We address a wide range of application use cases across our projects, including the discovery and prediction of functions and regulatory factors, biomedical and clinical evidence synthesis and automation, pre-trained large language and multi-modal model evaluation, extraction of data from clinical notes for predictive modelling, decision support, medical question answering, and interpretability and explanations for AI applications.

Clinical Areas

Our projects span a range of biomedical and clinical domains, including fundamental metabolism and metabolomics; drug discovery and molecular property prediction; RNA biology and regulatory interactions; oncology and personalised cancer biology; behavioural science and health psychology; mental health including anxiety, depression and psychosis; ophthalmology; infectious diseases; and physiotherapy.

Learn more about our projects

Contact and Collaboration

If you are interested in partnering with us, have an idea you’d like to discuss, or simply want to get in touch, we would love to hear from you! 

Please reach out via email to: janna.hastings@unisg.ch or janna.hastings@uzh.ch

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

Workshop report: “DSI meets USZ”

Combining the DSI and USZ expertise to tackle the digital transformation of healthcare

How to analyze text data from patient records? How to gain the trust of patients and potential donors of electronic health data to drive meaningful improvements in healthcare? How to implement virtual reality tools in a routine healthcare setting? Ten scientists from the Health Community of the Digital Society Initiative (DSI) presented their methodological skills and ongoing projects to an audience of researchers and staff members of the University Hospitals. The workshop’s mission was to bring the two communities closer and to foster collaborations.

The workshop featured discussions on various aspects of healthcare innovation and artificial intelligence in patient data processing. Topics included ethical challenges, principles for public trust in health data sharing, and a user-centered approach for personalized diabetes management. Stakeholder knowledge and implementation context were emphasized for successful innovation, and a vision for next-generation health studies integrating wearables and speech-to-text technologies was presented. The closing remarks expressed gratitude to collaborators and highlighted ongoing efforts in shaping collaborations within the DSI Health Community.

The DSI communities welcome new members and collaborations. So please join us in our endeavor to advance healthcare through digital transformation and collaborative efforts.