Search Results for author: Pau Herrero

Found 2 papers, 0 papers with code

Basal Glucose Control in Type 1 Diabetes using Deep Reinforcement Learning: An In Silico Validation

no code implementations18 May 2020 Taiyu Zhu, Kezhi Li, Pau Herrero, Pantelis Georgiou

In this work, we propose a novel deep reinforcement learning model for single-hormone (insulin) and dual-hormone (insulin and glucagon) delivery.

Q-Learning reinforcement-learning +1

Convolutional Recurrent Neural Networks for Glucose Prediction

no code implementations9 Jul 2018 Kezhi Li, John Daniels, Chengyuan Liu, Pau Herrero, Pantelis Georgiou

In addition, the model provides competitive performance in providing effective prediction horizon ($PH_{eff}$) with minimal time lag both in a simulated patient dataset ($PH_{eff}$ = 29. 0$\pm$0. 7 for 30-min and $PH_{eff}$ = 49. 8$\pm$2. 9 for 60-min) and in a real patient dataset ($PH_{eff}$ = 19. 3$\pm$3. 1 for 30-min and $PH_{eff}$ = 29. 3$\pm$9. 4 for 60-min).

Management

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