Chris Holmes
Professors of Biostatistics in Genomics
I have a broad interest in the theory, methods and applications of statistics and statistical modelling. My background and beliefs lie in Bayesian statistics which provides a unified framework to stochastic modelling and information processing. I am particularly interested in pattern recognition and nonlinear, nonparametric methods.
Recent publications
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To do no harm - and the most good - with AI in health care.
Journal article
Goldberg CB. et al, (2024), Nature medicine
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Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers
Journal article
Coppock H. et al, (2024), Nature Machine Intelligence
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Authors’ reply to the Discussion of ‘Martingale Posterior Distributions’
Journal article
Fong E. et al, (2023), Journal of the Royal Statistical Society. Series B: Statistical Methodology, 85, 1413 - 1416
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Martingale posterior distributions
Journal article
Fong E. et al, (2023), Journal of the Royal Statistical Society. Series B: Statistical Methodology, 85, 1357 - 1391
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Where Medical Statistics Meets Artificial Intelligence.
Journal article
Hunter DJ. and Holmes C., (2023), The New England journal of medicine, 389, 1211 - 1219