SOURCE-LINKED INTELLIGENCE

a toolkit for dynaMic health Impact analysiS to predicT disability-Related costs in the Aging population based on three case studies of steeL-industry exposed areas in europe

CORDIS · observation · Publication date unknown

lth policies and the monitoring of effects. A complete digital approach for HIA that could dynamically adapt to the variability of the determinants and their interaction is still poorly investigated. Artificial Intelligence algorithms offer innovative and high-performance possibilities for HIA implementations, improving elaboration and resizing of complex information and data. This proposal aims to develop a technological toolkit for dynamic, intelligent HIA toolkit to predict the health impact of health-related features, forecasting the trajectories of disability and quality of life reduction. This method will use environmental, socio-economic, geographical, and clinical characteristics, managed and elaborated with a federated learning architecture. The generated models will be adjusted for lifestyle and individual conditions data sourced from large population-based digital surveys. The models will be trained and validated on three different exposures to the steel plants' pollution: Taranto in southern Italy, Rybnik in Poland, and Flanders in Belgium. Pollution; Non-Communicable Dis

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recordType

award

status

SIGNED

region

EU

value

3619635

unit

EUR