1 citations · 2 across the 7 of their papers we have counts for
7 papers
A unified data format for managing diabetes time-series data: DIAbetes eXchange (DIAX)
Elliott C. Pryor, Marc D. Breton, Anas El Fathi
Diabetes devices, including Continuous Glucose Monitoring (CGM), Smart Insulin Pens, and Automated Insulin Delivery systems, generate rich time-series data widely used in research…
A Comparative Study of Transformer-Based Models for Multi-Horizon Blood Glucose Prediction
Meryem Altin Karagoz, Marc D. Breton, Anas El Fathi
Accurate blood glucose prediction can enable novel interventions for type 1 diabetes treatment, including personalized insulin and dietary adjustments. Although recent advances in…
Neural Networks for on-chip Model Predictive Control: a Method to Build Optimized Training Datasets and its application to Type-1 Diabetes
Alberto Castillo, Elliot Pryor, Anas El Fathi +2
Training Neural Networks (NNs) to behave as Model Predictive Control (MPC) algorithms is an effective way to implement them in constrained embedded devices. By collecting large amo…
Distribution-Based Sub-Population Selection (DSPS): A Method for in-Silico Reproduction of Clinical Trials Outcomes
Mohammadreza Ganji, Anas El Fathi, Chiara Fabris +3
Background and Objective: Diabetes presents a significant challenge to healthcare due to the negative impact of poor blood sugar control on health and associated complications. Com…
Attention Networks for Personalized Mealtime Insulin Dosing in People with Type 1 Diabetes
Anas El Fathi, Elliott Pryor, Marc D. Breton
Calculating mealtime insulin doses poses a significant challenge for individuals with Type 1 Diabetes (T1D). Doses should perfectly compensate for expected post-meal glucose excurs…
Intermittent Control for Safe Long-Acting Insulin Intensification for Type 2 Diabetes: In-Silico Experiment
Anas El Fathi, Mohammadreza Ganji, Dimitri Boiroux +2
Around a third of type 2 diabetes patients (T2D) are escalated to basal insulin injections. Basal insulin dose is titrated to achieve a tight glycemic target without undue hypoglyc…
Using Reinforcement Learning to Simplify Mealtime Insulin Dosing for People with Type 1 Diabetes: In-Silico Experiments
Anas El Fathi, Marc D. Breton
People with type 1 diabetes (T1D) struggle to calculate the optimal insulin dose at mealtime, especially when under multiple daily injections (MDI) therapy. Effectively, they will…