Population-scale networks to improve disease diagnosis and treatment - Privacy-preserving meta-learning of user models on graphs
Akronym
PRIMUS
Bidragets beskrivning
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.
Visa merStartår
2024
Slutår
2026
Beviljade finansiering
Rollen i Finlands Akademis konsortium
Finansiär
Finlands Akademi
Typ av finansiering
Akademiprojekt med särskild inriktning
Övriga uppgifter
Finansieringsbeslutets nummer
358958
Vetenskapsområden
Data- och informationsvetenskap
Forskningsområden
Tietojenkäsittelytieteet