Artificial intelligence with medical applications
The research group has long been working extensively on various forms of machine learning and artificial intelligence, mainly focusing on medical applications. Fundamental method development is combined with clinically motivated research focused on prediction and decision-making systems.
AI/ML research focuses on artificial neural networks and deep learning, with examples such as algorithms for imputation of missing data, survival analysis and generative modelling. The majority of the group's research is more directly linked to applications and arises in close collaboration with various partners, mainly in medicine but also in archaeology, for example.
Applications of machine learning on medical data include analysis, detection, prognosis or treatments for:
- breast and prostate cancer
- heart disease and heart transplants,
- autoimmune diseases; and
- neurodegenerative diseases.
The types of data used in the research include:
- classical biomarkers
- genomic and proteomic data and
- images from different imaging techniques.
The group originated in theoretical physics in the late 1980s, but now has a strong interdisciplinary focus where physics and computer science meet medicine. Several of the group's PhD students are co-supervised between the Faculty of Medicine and CEC.