EGI2024 Poster
Ignacio Lamata Martinez, Ville Tenhunen, Catalin Condurache


Using EGI FedCloud as a Platform of Data-Driven Risk Factor Prediction Models

Abstract

The LETHE project is about personalized prediction and intervention models for early detection and reduction of risk factors causing dementia, based on AI and distributed Machine Learning.

The project will establish novel digital biomarkers, for early detection of risk factors, based on unobtrusive ICT-based passive and active monitoring.  LETHE is leading to a more personalized risk factor prevention for persons in the initial stages of cognitive decline, thereby empowering people to an active and healthy lifestyle. Expansion of digital-enabled health preventive approaches, by reaching out to large populations, can save healthcare systems costs on expensive traditional interventions and confer benefits for the wider society.

In the LETHE project we are using the EGI FedCloud and other EOSC services as an infrastructure solution. In this poster we present an overview of the solution, its components and integrations. The EGI FedCloud is possible to use as a comprehensive sensitive data management solution where on the one hand it is possible to offer data processing and computing services, but on the other hand also offer the platform own applications of the organisation or the project.