| Information transfer by leaky, heterogeneous, protein kinase signaling systems M Voliotis, RM Perrett, C McWilliams, CA McArdle, CG Bowsher Proceedings of the National Academy of Sciences 111 (3), E326-E333, 2014 | 113 | 2014 |
| Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study E Carr, R Bendayan, D Bean, M Stammers, W Wang, H Zhang, T Searle, ... BMC medicine 19 (1), 1-16, 2021 | 85 | 2021 |
| Towards a decision support tool for intensive care discharge: machine learning algorithm development using electronic healthcare data from MIMIC-III and Bristol, UK CJ McWilliams, DJ Lawson, R Santos-Rodriguez, ID Gilchrist, ... BMJ open 9 (3), e025925, 2019 | 49 | 2019 |
| COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care RM Wood, CJ McWilliams, MJ Thomas, CP Bourdeaux, C Vasilakis Health care management science 23 (3), 315-324, 2020 | 42 | 2020 |
| The stability of multitrophic communities under habitat loss C McWilliams, M Lurgi, JM Montoya, A Sauve, D Montoya Nature Communications 10 (1), 1-11, 2019 | 25 | 2019 |
| The value of triage during periods of intense COVID-19 demand: Simulation modeling study RM Wood, AC Pratt, C Kenward, CJ McWilliams, RD Booton, MJ Thomas, ... Medical Decision Making 41 (4), 393-407, 2021 | 11 | 2021 |
| The dynamics of procalcitonin in COVID-19 patients admitted to Intensive care unit-a multi-centre cohort study in the South West of England, UK. P Williams, C McWilliams, K Soomro, I Harding, S Gurney, M Thomas, ... Journal of Infection 82 (6), e24-e26, 2021 | 10 | 2021 |
| Curation of an intensive care research dataset from routinely collected patient data in an NHS trust. C McWilliams, J Inoue, P Wadey, G Palmer, R Santos-Rodriguez, ... F1000Research 8, 2019 | 6 | 2019 |
| COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care: computer simulation study RM Wood, CJ McWilliams, MJ Thomas, CP Bourdeaux, C Vasilakis medRxiv, 2020 | 4 | 2020 |
| Requirements for a Bespoke Intensive Care Unit Dashboard in Response to the COVID-19 Pandemic: Semistructured Interview Study B Davidson, KMF Portillo, M Wac, C McWilliams, C Bourdeaux, ... JMIR Human Factors 9 (2), e30523, 2022 | | 2022 |
| Requirements for bespoke ICU Dashboard in response to the COVID-19 Pandemic. B Davidson, FP KM, M Wac, C McWilliams, C Bourdeaux, I Craddock JMIR Human Factors, 2022 | | 2022 |
| Supporting Patient Nutrition in Critical Care Units K Soomro, E Pimenidis, C McWilliams International Conference on Engineering Applications of Neural Networks, 128-136, 2022 | | 2022 |
| Predicting cause of death from free-text health summaries: development of an interpretable machine learning tool C McWilliams, EI Walsh, A Huxor, EL Turner, R Santos-Rodriguez medRxiv, 2021 | | 2021 |
| User-centric design of a clinical decision support system for critical care treatment optimisation. CJ McWilliams, IG Gilchrist, MJ Thomas, T Gould, RS Rodriguez, ... Proceedings DSRS-Turing’19. London, 21-22nd Nov, 2019, 2019 | | 2019 |
| Habitat loss and species interactions C MCWILLIAMS | | 2016 |
| Habitat loss and species interaction: an in silico investigation of the structure and dynamics of ecological communities C McWilliams University of Bristol, 2016 | | 2016 |
| Tangible Networks: A toolkit for exploring network science E Knoop, E Barter, AEM Villafranca, A Matyjaszkiewicz, C McWilliams, ... Proceedings of ECCS 2014, 33-43, 2016 | | 2016 |
| Sustainable Scotland: putting environmental justice at the heart of the policy agenda? E McDowell, C McWilliams WIT Transactions on Ecology and the Environment 93, 2006 | | 2006 |
| A machine learning approach to intensive care discharge. CJ McWilliams, DJ Lawson, R Santos-Rodriguez, ID Gilchrist, ... | | |
