Feasibility of AI-simulated patients for tailored selection of diabetes remission prediction models in metabolic bariatric surgery: a proof-of-concept study
This study demonstrates that LLM-generated simulated patients can refine a reproducible, transparent, and ethically safe algorithm for selecting diabetes remission prediction models, with future validation required using real-world clinical data.
Authors
- Matteo Monami (ORCID: https://orcid.org/0000-0001-9349-828X)
- RICARDO VITOR COHEN (ORCID: https://orcid.org/0000-0001-8779-3055)
- Mohammad Kermansaravi (ORCID: https://orcid.org/0000-0001-8978-9359)
Institutions
- Iran University of Medical Sciences (IR)
- Hospital Alemão Oswaldo Cruz (BR)
- Azienda Ospedaliero-Universitaria Careggi (IT)
Publication Details
- Journal
- Diabetology & Metabolic Syndrome
- Published
- 2025-12-17
- DOI
- https://doi.org/10.1186/s13098-025-02012-z
- Primary Topic
- Bariatric Surgery and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00