The talk will present recent advances in disease prediction through the integration of nationwide health data and genomic information. It will describe a foundation model trained on Finnish nationwide health data, covering more than 7 million individuals and 3 billion health events, to model and predict health trajectories. The talk will examine the current strengths and limitations of this approach, including challenges related to fairness and generalizability. It will then show how polygenic scores complement electronic-health-record-based prediction, with the two approaches providing distinct strengths across disease domains. Finally, the talk will discuss how integrating genomic and EHR data can improve trial emulation, strengthen causal inference, and improve biomarker discovery.
