Position of strength
AI and Health Data Science
Position of strength
AI and Health Data Science
Digital solutions alleviate pressure on the healthcare system
The healthcare system is facing major challenges in the future due to an aging population. This means an increasing disease burden and increased costs.
Digital solutions offer a huge opportunity to ease the pressure on the healthcare system – and this requires research.
The Faculty of Medicine has strong research environments in the Department of Health Science and Technology and the Department of Clinical Medicine that focus on research that can develop digital solutions to benefit patients in the healthcare system.
Support from development to implementation
Our research on health data science concerns the entire workflow for the development of digital solutions for the healthcare system, i.e. from the good idea, systems for data collection, development of AI and data-driven solutions to the implementation of solutions in clinical practice.
Prevention, early detection and personalized medicine
The research focuses on the prevention and early detection of disease based on analysis of individual risk profiles that can lead to lower treatment costs and better prognosis for patients. In addition, we contribute to the streamlining of clinical decision-making by introducing personalized medicine, which means that we can deliver more accurate diagnoses and treatment recommendations tailored to the individual patient.
Research areas
- Methods for prevention and detection of disease through effective use of existing data sources in the primary sector, such as municipal services, general practitioners and telemonitoring
- Predictive modelling for diagnostics, risk stratification and optimal treatment in e.g. cancer, diabetes, cardiovascular and cardiometabolic, inflammatory, neurological diseases. The models are based on multimodal data, including clinical data, biosignals, medical imaging data, molecular data and sensor-based data
- Development of language model-based solutions for efficiency across sectors, as well as foundational models for prediction of disease course with a view to optimizing treatment