Metadata-Version: 2.1
Name: py-replay-bg
Version: 0.0.2
Summary: ReplayBG is a digital twin-based methodology to assess new strategies for type 1 diabetes management.
Author-email: Giacomo Cappon <cappongiacomo@gmail.com>
Project-URL: Homepage, https://github.com/gcappon/py_replay_bg
Project-URL: Bug Tracker, https://github.com/gcappon/py_replay_bg/issues
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
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# PyReplayBG

The official Python porting of the ReplayBG software: [https://github.com/gcappon/replay-bg/](https://github.com/gcappon/replay-bg/).

<img src="https://i.postimg.cc/gJn8Sy0X/replay-bg-logo.png" width="250" height="250">

[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://github.com/gcappon/py_replay_bg/COPYING)
[![GitHub commit](https://img.shields.io/github/last-commit/gcappon/py_replay_bg)](https://github.com/gcappon/py_replay_bg/commits/master)

ReplayBG is a digital twin-based methodology to assess new strategies for type 1 diabetes management.

# Reference 

[G. Cappon, M. Vettoretti, G. Sparacino, S. Del Favero, A. Facchinetti, "ReplayBG: a digital twin-based methodology to identify a personalized model from type 1 diabetes data and simulate glucose concentrations to assess alternative therapies", IEEE Transactions on Biomedical Engineering, 2023, DOI: 10.1109/TBME.2023.3286856.](https://ieeexplore.ieee.org/document/10164140)
