This repository contains the code required to run a series of experiments on personalized forecasting of the glycemic curve or a sample patient.
Due to the confidentiality of source data, only code is and will be available, and as we know, it's very nice to have machine learning algorithms available, but they all amount to nothing if we have no idea about the problem it's designed for.
Anyway, this is just some playground on this sort of data for now. And if it helps you in any imaginable way, welcome it be!
- python >= 2.7
- numpy >= 1.14
- matplotlib >= 1.5.0
- docopt >= 0.6.0
- tqdm >= 4.19.0
- pytorch >= 0.3.1
The diabetes_forecasting package is licensed under the MIT "Expat" License:
Copyright (c) 2018: Ricardo Faundez-Carrasco.
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.