This use case leverages the AI4Gov tools to improve data completeness, transparency, and fairness in global rare disease research. By applying AI-driven analytics to patient-reported outcomes (PROs), the SDG Observatory identifies missing or biased data and visualises global disparities, supporting more equitable and evidence-based policymaking in healthcare.
Key points:
- Detection of missing and incomplete data in global rare disease datasets, revealing systemic data biases and underrepresented regions
- AI-driven analysis and visualisation of patient-reported outcomes (PROs) to identify disparities and data imbalances across countries
- Replicable methodology ensuring data fairness and inclusivity across all rare diseases
- Open-access dashboards for researchers, policymakers, and the public to explore global trends and inequalities
- Support for evidence-based policy decisions at EU, national, and global levels, promoting healthcare equity
- Integration of explainable AI (XAI) tools to ensure transparent and trustworthy analysis
- Contribution to SDG monitoring with bias-aware insights on global health data gaps
