| Convolutional recurrent neural networks for glucose prediction K Li, J Daniels, C Liu, P Herrero, P Georgiou IEEE Journal of Biomedical and Health Informatics 24 (2), 603-613, 2019 | 269 | 2019 |
| Deep learning for diabetes: a systematic review T Zhu, K Li, P Herrero, P Georgiou IEEE Journal of Biomedical and Health Informatics 25 (7), 2744-2757, 2020 | 154 | 2020 |
| GluNet: A deep learning framework for accurate glucose forecasting K Li, C Liu, T Zhu, P Herrero, P Georgiou IEEE journal of biomedical and health informatics 24 (2), 414-423, 2019 | 147 | 2019 |
| Linked electronic health records for research on a nationwide cohort of more than 54 million people in England: data resource A Wood, R Denholm, S Hollings, J Cooper, S Ip, V Walker, S Denaxas, ... BMJ 373 (n826), 2021 | 134 | 2021 |
| A Deep Learning Algorithm For Personalized Blood Glucose Prediction T Zhu, K Li, P Herrero, J Chen, G P. 27th International Joint Conference on Arti ficial Intelligence ( IJCAI 2018 …, 2018 | 129 | 2018 |
| Monitoring indirect impact of COVID-19 pandemic on services for cardiovascular diseases in the UK S Ball, A Banerjee, C Berry, JR Boyle, B Bray, W Bradlow, A Chaudhry, ... Heart 106 (24), 1890-1897, 2020 | 115 | 2020 |
| Nonlinear finite-time consensus-based connected vehicle platoon control under fixed and switching communication topologies Y Li, C Tang, K Li, S Peeta, X He, Y Wang Transportation Research Part C: Emerging Technologies 93, 525-543, 2018 | 110 | 2018 |
| An open-source platform for analyzing and sharing worm-behavior data A Javer, M Currie, CW Lee, J Hokanson, K Li, CN Martineau, E Yemini, ... Nature methods 15 (9), 645-646, 2018 | 107 | 2018 |
| Convolutional Compressed Sensing Using Deterministic Sequences K Li, L Gan, L Cong IEEE Trans. on Signal Processing 61 (3), 740 - 752, 2013 | 97 | 2013 |
| Dilated recurrent neural networks for glucose forecasting in type 1 diabetes T Zhu, K Li, J Chen, P Herrero, P Georgiou Journal of Healthcare Informatics Research 4, 308-324, 2020 | 96 | 2020 |
| Evaluating the performance of vehicular platoon control under different network topologies of initial states Y Li, K Li, T Zheng, X Hu, H Feng, Y Li Physica A: Statistical Mechanics and its Applications 450, 359-368, 2016 | 88 | 2016 |
| Basal Glucose Control in Type 1 Diabetes using Deep Reinforcement Learning: An In Silico Validation T Zhu, K Li, P Herrero, P Georgiou IEEE Journal of Biomedical and Health Informatics, 2020 | 87 | 2020 |
| Association of COVID-19 vaccines ChAdOx1 and BNT162b2 with major venous, arterial, or thrombocytopenic events: A population-based cohort study of 46 million adults in England WN Whiteley, S Ip, JA Cooper, T Bolton, S Keene, V Walker, R Denholm, ... PLoS medicine 19 (2), e1003926, 2022 | 64 | 2022 |
| The impact of the COVID-19 pandemic on cardiovascular disease prevention and management CE Dale, R Takhar, R Carragher, M Katsoulis, F Torabi, S Duffield, S Kent, ... Nature medicine 29 (1), 219-225, 2023 | 58 | 2023 |
| Dilated Recurrent Neural Network for Short-Time Prediction of Glucose Concentration J Chen, K Li, T Herrero, Zhu, P, G P. 27th International Joint Conference on Arti cial Intelligence ( IJCAI 2018 …, 2018 | 58 | 2018 |
| IoMT-enabled real-time blood glucose prediction with deep learning and edge computing T Zhu, L Kuang, J Daniels, P Herrero, K Li, P Georgiou IEEE Internet of Things Journal 10 (5), 3706-3719, 2022 | 57 | 2022 |
| An insulin bolus advisor for type 1 diabetes using deep reinforcement learning T Zhu, K Li, L Kuang, P Herrero, P Georgiou Sensors 20 (18), 5058, 2020 | 52 | 2020 |
| COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records JH Thygesen, C Tomlinson, S Hollings, MA Mizani, A Handy, A Akbari, ... The Lancet Digital Health 4 (7), e542-e557, 2022 | 50 | 2022 |
| Personalized blood glucose prediction for type 1 diabetes using evidential deep learning and meta-learning T Zhu, K Li, P Herrero, P Georgiou IEEE Transactions on Biomedical Engineering 70 (1), 193-204, 2022 | 37 | 2022 |
| Nonconvex compressed sensing by nature-inspired optimization algorithms F Liu, L Lin, L Jiao, K Li, S Yang, B Hou, H Ma, L Yang, J Xu IEEE transactions on cybernetics 45 (5), 1042-1053, 2015 | 35 | 2015 |
Pantelis GeorgiouImperial College London在 imperial.ac.uk 的电子邮件经过验证
