simglucose

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.

Pytorch Framework learning for deeplearning

Benchmark of glucose predictive models in diabetes

Differentiable simulators for Type 1 Diabetes research in Jax and PyTorch

Ingredient to Sugar Level Estimation (from training in Python to edge deployment in JS/TS)

A smart meal planner for everyone, including diabetics

Neural Networks for predicting diabetes from Fingerprints.

Chatbot for Diabetes. Focusing on nutrtion