Anas El Fathi

Research Assistant Professor

University of Virginia

United States

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Dr. Anas El Fathi is a Research Assistant Professor at the University of Virginia, USA. His research focuses on the development of advanced systems for managing type 1 diabetes, with recent articles exploring topics such as insulin dosing algorithms, closed-loop insulin delivery systems, and the application of neural networks in medical technology. He actively contributes to the field through innovative studies aimed at improving glucose monitoring and treatment outcomes for patients.

Articles (17)

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2025

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2025

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2021

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2021

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2020

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2020

Collaborators (2)

Robert Kearney

Professor

McGill University Faculty of Medicine

CANADA

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Jean‐François Yale

CANADA

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Anas El Fathi

Research Interests

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Articles (17)

A Bayesian decision support system for automated insulin doses in adults with type 1 diabetes on multiple daily injections: a randomized controlled trial

Miniaturized Neural Networks for Deploying Fully Closed Loop Insulin Delivery Systems: A Pilot Study Featuring Flexible Meal Announcement Options

Neural Networks for On-Chip Model Predictive Control: A Method to Build Optimized Training Datasets and its Application to Type-1 Diabetes

Accounting for Hypoglycemia Treatments in Continuous Glucose Metrics

The Virtual DCCT: Adding Continuous Glucose Monitoring to a Landmark Clinical Trial for Prediction of Microvascular Complications

Distribution-based sub-population selection (DSPS): A method for in-silico reproduction of clinical trials outcomes

Using Reinforcement Learning to Simplify Mealtime Insulin Dosing for People with Type 1 Diabetes: In-Silico Experiments

A Model-Based Insulin Dose Optimization Algorithm for People With Type 1 Diabetes on Multiple Daily Injections Therapy

Alleviating carbohydrate counting with a FiASP‐plus‐pramlintide closed‐loop delivery system (artificial pancreas): Feasibility and pilot studies

Reducing the need for carbohydrate counting in type 1 diabetes using closed‐loop automated insulin delivery (artificial pancreas) and empagliflozin: A randomized, controlled, non‐inferiority, crossover pilot trial

Fully Automated Artificial Pancreas for Adults With Type 1 Diabetes Using Multiple Hormones: Exploratory Experiments

Modelling glucose dynamics during moderate exercise in individuals with type 1 diabetes

Long-term use of the hybrid artificial pancreas by adjusting carbohydrate ratios and programmed basal rate: A reinforcement learning approach

A Meal Detection Algorithm for the Artificial Pancreas: A Randomized Controlled Clinical Trial in Adolescents With Type 1 Diabetes

Comparison between Closed-Loop Insulin Delivery System (the Artificial Pancreas) and Sensor-Augmented Pump Therapy: A Randomized-Controlled Crossover Trial

A Model-Based Insulin Dose Optimization Algorithm for People with Type 1 Diabetes on Multiple Daily Injections Therapy.

A pilot non‐inferiority randomized controlled trial to assess automatic adjustments of insulin doses in adolescents with type 1 diabetes on multiple daily injections therapy

Collaborators (2)

Robert Kearney

Jean‐François Yale

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