A generative artificial intelligence (AI) model trained on more than 10 million continuous glucose monitoring (CGM) measurements may help clinicians extract far more prognostic value from glucose traces than traditional metrics such as HbA1c, according to a study published in Nature. The model, called GluFormer, was developed using self-supervised learning on CGM data from 10,812 adults, most of whom did not have diabetes.