Patient-specific blood glucose prediction using deep learning, considering the challenges of "small dataset" and "data imbalance"

Source code for predicting Blood Glucose Concentration

The official implementation of the paper "Gluformer: Transformer-Based Personalized Glucose Forecasting with Uncertainty Quantification."

GluPredKit aims to make blood glucose model training and prediction more accessible.

The official implementation of the paper "GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks."

"Personalised Short-Term Glucose Prediction via Recurrent Self-Attention Network" in CBMS 2021

Benchmark of glucose predictive models in diabetes

Implementation of architecture for 2020 OhioT1D competition submission. Includes weights from pre-training runs with Tidepool data set. Baseline architecture is N-BEATS, modifications include RNN/shared output blocks, additional Losses. https://folk.idi.ntnu.no/kerstinb/kdh/KDH_ECAI_2020_Proceedings.pdf

"Jointly Predicting Postprandial Hypoglycemia and Hyperglycemia Using Continuous Glucose Monitoring Data in Type 1 Diabetes" in EMBC 2023

Machine learning web app to predict user glucose levels

Data Science Project - Predicting glucose levels with data collected by non-invasive wearable device

Applying deep learning to glucose prediction