115 citations · 125 across the 3 of their papers we have counts for
4 papers
A novel hand-held interface supporting the self-management of Type 1 diabetes
Robert Spence, Chukwuma Uduku, Kezhi Li +2
The paper describes the interaction design of a hand-held interface supporting the self-management of Type 1 diabetes. It addresses well-established clinical and human-computer int…
Basal Glucose Control in Type 1 Diabetes using Deep Reinforcement Learning: An In Silico Validation
Taiyu Zhu, Kezhi Li, Pau Herrero +1
People with Type 1 diabetes (T1D) require regular exogenous infusion of insulin to maintain their blood glucose concentration in a therapeutically adequate target range. Although t…
A Dual-Hormone Closed-Loop Delivery System for Type 1 Diabetes Using Deep Reinforcement Learning
Taiyu Zhu, Kezhi Li, Pantelis Georgiou
We propose a dual-hormone delivery strategy by exploiting deep reinforcement learning (RL) for people with Type 1 Diabetes (T1D). Specifically, double dilated recurrent neural netw…
Convolutional Recurrent Neural Networks for Glucose Prediction
Kezhi Li, John Daniels, Chengyuan Liu +2
Control of blood glucose is essential for diabetes management. Current digital therapeutic approaches for subjects with Type 1 diabetes mellitus (T1DM) such as the artificial pancr…