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Thygesen, JH, Tomlinson, C, Hollings, S, Mizani, MA, Handy, A, Akbari, A, Banerjee, A, Cooper, J, Lai, AG, Li, K, Mateen, BA, Sattar, N, Sofat, R, Torralbo, A, Wu, H, Wood, A, Sterne, JAC, Pagel, C, Whiteley, WN, Sudlow, C, Hemingway, H, Denaxas, S, National Core Study and the CVD-COVID-UK/COVID-IMPACT Consortium, Longitudinal Health and Wellbeing COVID-19 and Mamas, MA ORCID: https://orcid.org/0000-0001-9241-8890 (2022) COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records. The Lancet Digital Health, 4 (7). e542 - e557.
Cao, J ORCID: https://orcid.org/0000-0001-5099-9914, Harrold, D, Fan, Z ORCID: https://orcid.org/0000-0002-5575-1536, Morstyn, T, Healey, D and Li, K (2020) Deep Reinforcement Learning Based Energy Storage Arbitrage With Accurate Lithium-ion Battery Degradation Model. IEEE Transactions on Smart Grid, 11 (5). pp. 4513-4521.
MacCormick, IJC, Williams, BM, Zheng, Y, Li, K, Al-Bander, B ORCID: https://orcid.org/0000-0002-2518-7364, Czanner, S, Cheeseman, R, Willoughby, CE, Brown, EN, Spaeth, GL and Czanner, G (2019) Accurate, fast, data efficient and interpretable glaucoma diagnosis with automated spatial analysis of the whole cup to disc profile. PLoS One, 14 (1). e0209409 - e0209409.