GlucoFM: Foundation model for continuous glucose monitoring
Google Research ● Covered by 2 sources
GlucoFM was developed as a self-supervised foundation model for continuous glucose monitoring that separates slow glycemic trends from short-term deviations while accounting for time of day and missing data. It was pre-trained on 109,066 hours of unlabeled CGM data and, across 14 cohort–task evaluations, achieved an average PR-AUC of 58.8% versus 54.7% for the best GluFormer baseline variant, and 21.88 mg/dL MAE for two-hour post-meal glucose-change forecasting. The model improved diabetes-risk, beta-cell-dysfunction, and most insulin-resistance predictions, transferred well across cohorts, and adapted with very limited labeled data.
Why it matters
Health & Bioscience