Matthys Potgieter and Vincent Meurrens | EPCON BV
Competition Sponsor: EIT Health
Awardee Year: 2020
EPCONs technology uses unsupervised learning models to generate a digital twin of the real world, using climate and geographical features, sociological data, historical health records and programmatic data. Our platform will then identify disease patterns throughout the complex data and generate spatiotemporal models of historical outbreaks, and in combination with present case notifications identifies areas, population groups and individuals at risk and estimated prevalence across the region. This data and platform will serve to assess healthcare readiness, plan interventions, help in screening of presumptive cases and inform exposed individuals with increased risk.
To learn more about this proposal, email healthylongevity@nas.edu.