The Research Centre for Digital Medicine (REDM) focuses on the clinical application and implementation of digital and electronic technologies, clinical decision support systems, and novel applications of artificial intelligence and machine learning in healthcare and biomedicine. Characteristic of REDM is its problem-driven, multidisciplinary approach, aimed at establishing robust and tailored methodologies suitable for clinical practice, both general and personalized, while integrating clinical, technical and scientific perspectives.

Research is organised around several areas. Biostatistics and Epidemiology focuses on the intersection of medical science, advanced technology and quantitative modelling, developing new machine-learning techniques and epidemiological approaches within pharmaco-epidemiology and other biomedical applications, supporting research ranging from risk estimation and drug-safety assessment to biomarker discovery and dynamic patient monitoring. Big Data and Digital Health Data Platforms uses hospital data platforms to advance research in clinical decision support and health-data intelligence, linking large administrative datasets to enable prediction modelling at population scale and detailed analysis of care pathways, cost-effectiveness and service utilisation.

Innovation and Evaluation of Health Care Services is anchored in clinical work at the university hospital, driving data-driven research into innovative radiation sensitising strategies and digital concepts such as radiomics, as well as an interuniversity project on magnetic resonance diffusion and perfusion for the characterisation of healthy and pathologic tissues. This work also addresses the potential impact of improved clinical decision making and predictive modelling on costs and effectiveness, and supports informed and shared decisions about e-Health solutions to improve patient well-being, particularly for vulnerable patients such as the elderly and those with lower health literacy.