Extended Data Fig. 5: Integrating Delphi-2M predictions with other data types.
From: Learning the natural history of human disease with generative transformers
Results of a linear regression model that uses Delphi logits and additional features to predict 5-year disease occurrence for selected diseases. Shown is the average validation AUC across 5-year age groups ranging from 40 to 80 years of age, additionally stratified by sex. All models use sex and age as additional covariates. For prediction, only data before recruitment was used. As additional features, models use polygenic risk scores (PRS, a), 57 biomarkers used in the MILTON study (b) and UKB field 2178 Overall health rating status (c).
