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University of Cambridge > Talks.cam > Computer Laboratory Wednesday Seminars > Machine learning for medicine: Predicting, pre-empting and treating disease
![]() Machine learning for medicine: Predicting, pre-empting and treating diseaseAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact jo de bono. In this talk, I will give an overview of our research work on developing state-of-the-art machine learning & AI theory and methods aimed at providing actionable intelligence to patients, clinicians, medical researchers, and healthcare providers. This will include a discussion of our work on automated machine learning for the design of models for predicting clinical risk (AutoPrognosis), on leveraging multiple datasets to improve target-specific predictive models using Generative Adversarial Networks (RadialGAN) and on the fundamental theory and methods for causal inference and individualized treatment effects. More about our work can be found at: http://medianetlab.ee.ucla.edu Video recording of the talk (restricted to UCam users): https://www.cl.cam.ac.uk/seminars/wednesday/video/lt1-181010-wed-1600-t111904-only-ucam.html This talk is part of the Computer Laboratory Wednesday Seminars series. This talk is included in these lists:
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