The FinRegistry project leverages nationwide health and socio-demographic registry data to explore comprehensive risk trajectories and uses this information to develop statistical and machine learning models to predict disease occurrences from registry data.
This project will use the complex relationship between health outcomes, medications, socio-demographic information, and familial risk to provide new epidemiological and biological hypotheses that can then be directly followed up with more targeted studies.
Results of this study can support future research to develop personalized health care based on disease-specific prediction models.
We are welcoming collaborations!
Want to collaborate?
If your research project is within the scope of our proposal, contact us!
Otherwise, considering applying to registry data via Findata.