Verify demographic generalization

Background: The current model, SpiroLLM, was trained and validated predominantly on data from the UK Biobank, which is known to be largely composed of white British participants.

Question / Future Work: The generalizability and algorithmic fairness of SpiroLLM must be verified by validating its performance across multi-center, multi-ethnic cohorts from diverse racial groups outside of the UK Biobank population.

Why It Matters: Lack of demographic diversity in training data limits the model’s applicability and fairness across global populations, a critical consideration for clinical tools.

Evidence: First, to enhance universality and algorithmic fairness, we plan to validate SpiroLLM across multi-center, multi-ethnic cohorts, expanding beyond the UK Biobank population to ensure robustness across diverse racial groups.