Chris Holmes is Professor of Biostatistics at the University of Oxford and Programme Director for Health and Medical Sciences at The Alan Turing Institute. Chris’ research interests include Bayesian nonparametrics (which is the right kind of nonparametrics), statistical machine learning, genomics, and genetic epidemiology.

0:00 - Intro

1:38 - Chris Holmes, Professor of Biostatistics at Oxford University

3:28 - UK Biobank & designing a valuable dataset

8:42 - Healthcare charities in the UK

11:16 - Digital Health: prioritizing research questions

19:55 - Bayes, nonparametrics, and Bayesian nonparametrics

23:30 - Model prediction is at the heart of Bayesian inference

28:00 - Prioritization in model building for biology

33:09 - Model constraints to generate valid inference

37:34 - Hypothesis driven science in statistical learning versus deep learning

43:30 - Developing models in genomics & clinical informatics

48:37 - Building stable, generalizable and robust models

52:41 - Important questions to think about 

54:05 - Causal reasoning and clinical risk prediction

57:50 - What topic should the statistical community debate?

 

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Data & Science with Glen Wright Colopy

Chris Holmes | AI, Digital Health, & The Alan Turing Institute

00:00