2021
Carr, E; Bendayan, R; Bean, D; Stammers, M; Wang, W; Zhang, H; Searle, T; Kraljevic, Z; Shek, A; Phan, H T T; Muruet, W; Gupta, R K; Shinton, A J; Wyatt, M; Shi, T; Zhang, X; Pickles, A; Stahl, D; Zakeri, R; Noursadeghi, M; O'Gallagher, K; Rogers, M; Folarin, A; Karwath, Andreas; Wickstrøm, K E; Köhn-Luque, A; Slater, L; Cardoso, V R; Bourdeaux, C; Holten, A R; Ball, S; McWilliams, C; Roguski, L; Borca, F; Batchelor, J; Amundsen, E K; Wu, X; Gkoutos, G V; Sun, J; Pinto, A; Guthrie, B; Breen, C; Douiri, A; Wu, H; Curcin, V; Teo, J T; Shah, A M; Dobson, R J B
Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study Journal Article
In: BMC Med, vol. 19, no. 1, pp. 23, 2021, ISSN: 1741-7015.
Links | BibTeX | Tags: artificial intelligence, COVID-19, early warning score, health data science, machine learning
@article{RN19,
title = {Evaluation and improvement of the National Early Warning Score (NEWS2) for COVID-19: a multi-hospital study},
author = {E Carr and R Bendayan and D Bean and M Stammers and W Wang and H Zhang and T Searle and Z Kraljevic and A Shek and H T T Phan and W Muruet and R K Gupta and A J Shinton and M Wyatt and T Shi and X Zhang and A Pickles and D Stahl and R Zakeri and M Noursadeghi and K O'Gallagher and M Rogers and A Folarin and Andreas Karwath and K E Wickstrøm and A Köhn-Luque and L Slater and V R Cardoso and C Bourdeaux and A R Holten and S Ball and C McWilliams and L Roguski and F Borca and J Batchelor and E K Amundsen and X Wu and G V Gkoutos and J Sun and A Pinto and B Guthrie and C Breen and A Douiri and H Wu and V Curcin and J T Teo and A M Shah and R J B Dobson},
doi = {10.1186/s12916-020-01893-3},
issn = {1741-7015},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {BMC Med},
volume = {19},
number = {1},
pages = {23},
keywords = {artificial intelligence, COVID-19, early warning score, health data science, machine learning},
pubstate = {published},
tppubtype = {article}
}
2020
Wu, H; Zhang, H; Karwath, Andreas; Ibrahim, Z; Shi, T; Zhang, X; Wang, K; Sun, J; Dhaliwal, K; Bean, D; Cardoso, V R; Li, K; Teo, J T; Banerjee, A; Gao-Smith, F; Whitehouse, T; Veenith, T; Gkoutos, G V; Wu, X; Dobson, R; Guthrie, B
Ensemble learning for poor prognosis predictions: a case study on SARS-CoV2 Journal Article
In: J Am Med Inform Assoc, 2020, ISSN: 1067-5027 (Print) 1067-5027.
Links | BibTeX | Tags: artificial intelligence, COVID-19, health data science, machine learning
@article{RN18,
title = {Ensemble learning for poor prognosis predictions: a case study on SARS-CoV2},
author = {H Wu and H Zhang and Andreas Karwath and Z Ibrahim and T Shi and X Zhang and K Wang and J Sun and K Dhaliwal and D Bean and V R Cardoso and K Li and J T Teo and A Banerjee and F Gao-Smith and T Whitehouse and T Veenith and G V Gkoutos and X Wu and R Dobson and B Guthrie},
doi = {10.1093/jamia/ocaa295},
issn = {1067-5027 (Print) 1067-5027},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {J Am Med Inform Assoc},
keywords = {artificial intelligence, COVID-19, health data science, machine learning},
pubstate = {published},
tppubtype = {article}
}