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Article

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.

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