Population-scale networks to improve disease diagnosis and treatment - Privacy-preserving meta-learning of user models on graphs

Description of the granted funding

We aim at enabling better treatment of diseases by taking into account the information in the family and other networks of patients, and more generally ask how can risk assessments and treatments be best improved by taking into account the unique population-wide data of Finland. This requires developing new machine learning methods, and developing them to be privacy-preserving. We start with the leading cause of death in Finland, cardiovascular diseases, and develop the methods to be applicable not only to other diseases but also more widely in personalized decision making problems across fields.
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Starting year

2024

Granted funding



Markus Perola Orcid -palvelun logo
63 964 €

Funder

Research Council of Finland

Funding instrument

Targeted Academy projects

Other information

Funding decision number

359072

Fields of science

Computer and information sciences

Research fields

Tietojenkäsittelytieteet

Identified topics

public health, occupational health