Machine learning and engagement insights for personalized blood glucose management
Machine learning can reveal distinct glycemic trajectories moderated by demographic, clinical, and engagement factors. These findings underscore the potential of digital health platforms to personalize diabetes care and improve blood glucose management through adaptive, data-driven strategies.
Authors
- Omar Manejwala
- Inbar Breuer Asher
- Yifat Fundoiano-Hershcovitz
- David L. Horwitz
Institutions
- FIT Consulting (Italy) (IT)
- Northern Territory Health Services (AU)
- BH Consulting (Ireland) (IE)
Publication Details
- Journal
- Frontiers in Digital Health
- Published
- 2026-02-24
- DOI
- https://doi.org/10.3389/fdgth.2026.1660815
- Primary Topic
- Diabetes Management and Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00