search

RobotPsychologist / bg_control

Improving short-term prandial blood glucose outcomes for people with type 1 diabetes, a complex disease that affects nearly 10 million people worldwide. We aim to leverage semi-supervised learning to identify unlabelled meals in time-series blood glucose data, develop meal-scoring functions, and explore causal machine-learning techniques.
3 stars 35 forks source link

Glycemic Index and Glycemic Load Datasets #39

Open RobotPsychologist opened 4 hours ago

RobotPsychologist commented 4 hours ago

Incorporating glycemic load and glycemic index datasets could improve our modeling. We should automate incorporating the data from some open-source datasets into our project:

https://world.openfoodfacts.org/data

https://fdc.nal.usda.gov/download-datasets.html

It is also worth investigating if more data sources are available and scrapable.

RobotPsychologist commented 4 hours ago

@andytubeee

RobotPsychologist commented 4 hours ago

Building API connections to

https://platform.fatsecret.com/docs/guides

and

https://developer.nutritionix.com/docs/v2

To populate our estimated GI and GL distribution of logged meals.