Toward fully algorithmic care for type 1 diabetes: The case for AI autonomy, and a recalibrated role for the diabetologist in an ageing type 2 diabetes population
Artificial intelligence can already automate selected diabetes tasks, but the evidence is uneven. Automated insulin delivery is established in type 1 diabetes; in type 2 diabetes, validated screening and insulin-adjustment tools support a tiered, human-governed model rather than wholesale autonomy.
Authors
- Dured Dardari (ORCID: https://orcid.org/0000-0002-7172-4300)
- Randa Dardari
- Islam Maaz
- Helene Dardari
- Mounzer Maaz
- Samar Maaz
Institutions
- University of Aleppo (SY)
- Pediatric Oncology Group (CA)
- Carol Davila University of Medicine and Pharmacy (RO)
- Université Paris-Saclay (FR)
- Centre Hospitalier Sud Francilien (FR)
- Université d'Évry Val-d'Essonne (FR)
Publication Details
- Journal
- PLOS Digital Health
- Published
- 2026-09-18
- DOI
- https://doi.org/10.1371/journal.pdig.0001734
- Primary Topic
- Diabetes Management and Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00