New model improves short- and long-term disease risk prediction
 

Researchers developed ALADYNOULLI, a Bayesian generative model that combines longitudinal health records, age, and polygenic risk to identify reproducible disease signatures across more than 683,000 participants. In UK Biobank testing, the framework achieved stronger short- and long-term risk discrimination than established clinical scores while revealing disease subgroups and genetic associations.

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