Project Details
Description
With BEE, we recognize the significant impact of environmental exposures such as air and noise pollution, green spaces on health, and the role of socioeconomic disparities. We aim to leverage a holistic exposomic approach to integrating comprehensive environmental, medical, and socioeconomic data to research the possibility of applying (1) an innovative AI-driven model for predicting acute CVD and NVD risks and (2) applying causal inference methods to examine the causal effects of the urban exposome on chronic CVD and NVD risks, eventually extending to other non-communicable diseases (NCDs).
| Short title or EU acronym | BEE |
|---|---|
| Acronym | BRGRD96 |
| Status | Active |
| Effective start/end date | 1/09/25 → 31/08/28 |
Keywords
- chronic disease data
- AI-driven model
Flemish discipline codes in use since 2023
- Artificial intelligence not elsewhere classified
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