FinRegistry uses nationwide registry data to build machine learning models that will help to better understand and predict the onset of diseases in the population of Finland
FinRegistry is a joint research project of the Finnish Institute for Health and Welfare (THL) and the Data Science Genetic Epidemiology research group at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki.
The project aims to develop new ways to model the complex relationships between health and risk factors. To do that we develop statistical and machine learning models to understand and predict disease occurrences using high-resolution longitudinal data.
FinRegistry utilizes the unique registry system in Finland to combine health data with a wide range of other information from nearly the whole population of Finland.
Visit also the main THL page for this project at