---
tags:
  - iints/source
  - iints/source/model
source_id: "mujahid_2024_generative_t1d_simulator"
source_bucket: "packaged_evidence"
category: "model"
component: "simulation_realism"
url: "https://doi.org/10.1038/s43856-024-00476-0"
doi: "10.1038/s43856-024-00476-0"
status: active
---

# Generative deep learning for the development of a type 1 diabetes simulator

> [!info] What this source supports
> Reference for modern data-driven T1D simulator realism framing and the limits of purely physiological approximations.

| Field | Value |
| --- | --- |
| Source ID | `mujahid_2024_generative_t1d_simulator` |
| Bucket | `packaged_evidence` |
| Category | `model` |
| SDK component | `simulation_realism` |
| DOI | 10.1038/s43856-024-00476-0 |
| URL | https://doi.org/10.1038/s43856-024-00476-0 |
| Origin file | `src/iints/presets/evidence_sources.yaml` |

## Citation

Mujahid O, Contreras I, Beneyto A, Vehi J. Commun Med (Lond). 2024;4:51.

## User Interpretation

Use this source to explain **why the SDK default, metric, dataset, or hardware-safety boundary exists**. It is evidence support for pre-clinical simulation and documentation, not a medical approval claim.
