Clinical AI
The clinical AI group
The group focuses on the development and implementation of machine learning (ML) applications in the healthcare sector and health data infrastructures, primarily within cancer.
Development and implementation of ML applications
We work on bringing artificial intelligence (AI) to the clinic by developing ML-based dynamic risk prediction models and implementing them in decision support tools. These models primarily rely on real-world data from clinical and administrative registers.
Multimodal AI
We also work on models integrated multiple modalities notably incorporating 3D-imaging and text from journal notes, alongside structured clinical data. We work with natural language processing (NLP) to extract information from unstructured medical texts, notably with large language models (LLMs).
Health data infrastructure
We also conduct and participate in projects aiming at facilitating research, data and knowledge sharing, and AI implementation at the regional, national, and European level. This includes a precision medicine platform and work with the findability, accessibility, interoperability, and reusability (FAIR) data principles and observational medical outcomes partnership (OMOP) common data model.