A foundation model for continuous glucose monitoring data
Nature • • health
Key Points:
- Recent advances in continuous glucose monitoring (CGM) technology and analytics have enhanced understanding of glycemic variability and its impact on diabetes management, as highlighted by multiple studies including those by Shilo et al. (2024) and Battelino et al. (2023).
- Foundation models and self-supervised learning approaches are increasingly applied in medical imaging and time series data, improving disease detection and personalized health interventions, as demonstrated in works by Zhou et al. (2023), Chen et al. (2024), and Yuan et al. (2024).
- Large-scale longitudinal cohort studies such as the 10 K study in Israel (Shilo et al., 2021) and global burden analyses (GBD 2021 Diabetes
