A pre-clinical Edge-AI SDK for diabetes management validation.
Project description
IINTS-AF SDK
"Code shouldn't be a secret when it's managing a life."
Open-source research platform for insulin delivery algorithm simulation and validation.
What It Does
- Simulate virtual patients across thousands of scenarios before any algorithm reaches a real device
- Certify datasets cryptographically — traceable, consented, reproducible
- Understand results with audit-ready reports and local AI explanation via Ministral
Install
pip install "iints-sdk-python35[full,mdmp]"
iints doctor --smoke-run
Raspberry Pi / Arduino UNO Q:
pip install "iints-sdk-python35[edge,mdmp]"
iints edge quickstart --board raspberry_pi
iints edge quickstart --board uno_q
Quick Start
iints quickstart --project-name my_study
cd my_study
iints presets run --name baseline_t1d --algo algorithms/example_algorithm.py
iints ai report results/<run_id>
Full documentation: python35.github.io/IINTS-SDK
Live Demo
For a Zoom call, jury walkthrough, or sponsor demo where you want to show both the code and the generated outputs in one terminal flow:
iints demo-live --output-dir results/live_demo
That exports the showable demo script, prints the key SDK calls, runs the demo, and lists the poster plus proof artifacts to open next.
Research software. Not a medical device. MIT Licensed.
Built by a 17-year-old with type 1 diabetes.
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