OxTalks will soon move to the new Halo platform and will become 'Oxford Events.' There will be a need for an OxTalks freeze. This was previously planned for Friday 14th November – a new date will be shared as soon as it is available (full details will be available on the Staff Gateway).
In the meantime, the OxTalks site will remain active and events will continue to be published.
If staff have any questions about the Oxford Events launch, please contact halo@digital.ox.ac.uk
Utilizing data from Finland, where genetic details of approximately 500,000 individuals are linked to a national health registry, this presentation will explore the use of polygenic scores and electronic health records (EHRs) to predict disease susceptibility and progression. It will highlight the challenges and successes of employing polygenic scores in clinical trial design, emphasizing their potential to enhance trial efficiency and cost-effectiveness. Additionally, the talk will discuss the application of machine learning algorithms to predict healthcare outcomes from EHRs, assessing their fairness and generalizability across different populations. The presentation will conclude with a direct comparison of genetic and EHR-based predictions to assess which approach is most predictive and generalizable across healthcare systems.
Associate Professor at FIMM and HiLIFE and a research associate at Harvard Medical School and Massachusetts General Hospital. Previously he did his post-doc at the Analytical and Translation Genetic Unit at Massachusetts General Hospital/Harvard Medical School/Broad Institute and his PhD at Karolinska Institute. His research interests lie at the intersection between epidemiology, genetics and statistics. His research vision is to integrate genetic data and information from electronic health record/national health registries to enhance early detection of common diseases and enable more effective public health interventions.
