Artificial intelligence algorithm for predicting cardio-cerebrovascular risk in type 2 diabetes: concordance with clinical and instrumental assessments
A marked difference was observed in the algorithm's performance. While the AI showed strong predictive ability for cerebrovascular complications, it failed to reliably predict heart disease risk. These results suggest that the algorithm may be clinically valuable for cerebrovascular risk assessment but needs refinement for cardiac prediction.
Authors
- Francesco Piarulli (ORCID: https://orcid.org/0000-0002-1193-4410)
- Annunziata Lapolla (ORCID: https://orcid.org/0000-0002-9207-7704)
- Eugenio Ragazzi (ORCID: https://orcid.org/0000-0002-0390-6823)
- Giovanni Sartore (ORCID: https://orcid.org/0000-0001-5753-7114)
- Chiara Celeste Celsan
Institutions
- University of Padua (IT)
Publication Details
- Journal
- Diabetology & Metabolic Syndrome
- Published
- 2025-08-27
- DOI
- https://doi.org/10.1186/s13098-025-01910-6
- Citations
- 2
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 5.88
Funders
- Università degli Studi di Padova