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Publications by Statistical Genetics and Epidemiology

Our research spans areas of statistical genetics, in particular the development of powerful statistical approaches to analyse genetic data, as well as studying infectious diseases.

Stricker, M. et al. (2024) “Genome-wide classification of epigenetic activity reveals regions of enriched heritability in immune-related traits.”, Cell genomics, 4(3), p. 100508.
Goldberg, C. et al. (2024) “To do no harm — and the most good — with AI in health care”, Nature Medicine, 30(3), pp. 623–627.
Hampshire, A. et al. (2024) “Cognition and Memory after Covid-19 in a Large Community Sample”, New England Journal of Medicine, 390(9), pp. 806–818.
Spitschan, M. et al. (2024) “Power Analysis for Human Melatonin Suppression Experiments”, Clocks & Sleep, 6(1), pp. 114–128.
Liu, X. et al. (2024) “Directrices para presentación de informes de ensayos clínicos sobre intervenciones con inteligencia artificial: extensión CONSORT-AI”, BULL PAN AM HEALTH ORGAN, 48, p. e13.
Coppock, H. et al. (2024) “Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers”, Nature Machine Intelligence, 6(2), pp. 229–242.
Coppock, H. et al. (2024) “Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers”, Nature Machine Intelligence, 6(2), pp. 229–242.
Rivera, L. et al. (2024) “Clinical and epidemiological characteristics of Madariaga and Venezuelan equine encephalitis virus infections”, p. 2024.02.02.24302220.
Fong, E., Holmes, C. and Walker, S. (2024) “Martingale posterior distributions”, Journal of the Royal Statistical Society Series B (Statistical Methodology), 85(5), pp. 1357–1391.
Fong, E., Holmes, C. and Walker, S. (2024) “Authors’ reply to the Discussion of ‘Martingale Posterior Distributions’”, Journal of the Royal Statistical Society Series B (Statistical Methodology), 85(5), pp. 1413–1416.