no code implementations • 26 Feb 2024 • Chengzhe Piao, Taiyu Zhu, Stephanie E Baldeweg, Paul Taylor, Pantelis Georgiou, Jiahao Sun, Jun Wang, Kezhi Li
Accurate prediction of future blood glucose (BG) levels can effectively improve BG management for people living with diabetes, thereby reducing complications and improving quality of life.
no code implementations • 12 Aug 2022 • William J Bolton, Cosmin Badea, Pantelis Georgiou, Alison Holmes, Timothy M Rawson
Artificial intelligence (AI) assisting with antimicrobial prescribing raises significant moral questions.
no code implementations • 18 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.
no code implementations • 9 Oct 2019 • 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).
no code implementations • 9 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).