Project Team

Margrethe Bang Henriksen

Postdoctoral researcher and medical doctor in specialist training in oncology. She works with data-driven approaches to early detection and risk prediction of disease, combining registry data, clinical data, and biomarkers.

Her work contributes to the development of machine learning models and the use of explainable AI to identify key risk factors. She is also involved in linking and analysing large-scale datasets and in developing methods for extracting structured information from clinical text using NLP.

Claus Lohman Brasen

Chief Physician, specialist in clinical biochemistry with a PhD in medical genetics, working at the intersection of biomarkers, registry and activity data, mainly focusing on the use of blood-based biomarkers for early detection and risk prediction of disease.

His work contributes to integrating clinical and laboratory data into large-scale data platforms and to developing predictive models for major non-communicable diseases (NCDs) and emergency medicine in collaboration with data scientists. He is also working with natural language processing (NLP) to extract structured information from clinical text, supporting the use of unstructured data in large-scale analyses.

Akam Petersen

PhD and data scientist with a focus on artificial neural network (ANN) and machine learning (ML), including medical image recognition. He develops advanced methods for analysing complex, high-dimensional data types and contributes to scalable modelling approaches and solutions.

His work supports the integration of diverse data sources and the development of transparent and reproducible models.

Ricco Flyckt

Data scientist working with large-scale and heterogeneous health data to develop predictive models for major non-communicable diseases (NCDs). His work includes building research cohorts from the ground up, preparing and harmonising complex datasets, and testing different machine learning approaches for risk prediction.

He contributes to the development of robust and reusable analytical pipelines within a secure data infrastructure.

Anna Krogshave Dahlgren

She works with large-scale registry data and social network analysis to understand behavioural patterns related to health and disease. She also develops machine learning models and performs statistical analyses to identify risk factors and patterns in complex data. Her PhD will focus on changes in health behaviour among relatives of patients, contributing to the development of data-driven insights and survey instruments.

Torben F. Hansen

Medical doctor and professor with extensive experience in clinical cancer research and translational medicine. He provides scientific supervision and overall strategic leadership for the pilot, ensuring that the activities are clinically relevant and aligned with the broader project goals.

He serves as a key link between the overarching research strategy, external stakeholders and the practical implementation of pilot activities, helping to prioritise focus areas and translate data-driven insights into clinical value.