Associate Professor Andrea Ganna from the Institute for Molecular Medicine Finland (FIMM) at the University of Helsinki uses large datasets to identify the demographic and genetic traits that underlie common and complex diseases. AI can make a risk calculation for each individual by modelling data from longitudinal tracking of diseases and medications along with genetic, family and demographic data. Once the data has been collected from different registers, the individual data is encrypted and stored in the sensitive data services of the Finnish ELIXIR node of the CSC - IT Center for Science.
The dataset contains data from 7.2 million individuals, i.e. the entire population of Finland and many relatives who have already died. It contains a lot of different, wide-ranging information, including health information, information on family relationships, socio-economic information, and laboratory results and prescriptions.
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ELIXIR is partly funded by the European Commission