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Time: The next frontier in causal machine learning

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If you have a question about this talk, please contact Peter Watson .

: Mihaela will talk about the work of her lab in developing cutting-edge machine learning (ML) methods to apply to real-world problems in medicine and healthcare in areas such as prostate, breast and skin cancers, cystic fibrosis, beta-blocker use in hypertension, coronary heart disease and COVID -19. The work encompasses a very large range of areas associated with ML including deep learning, decision trees, causal inference, time series data analysis and statistical machine learning. Mihaela will also explore the role that statistics plays in underpinning machine learning in order to make data-driven decisions.

This talk is part of the Cambridge Statistics Discussion Group (CSDG) series.

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