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February 2019

BSU Seminar: “Sample size considerations for the design clinical trials – quantifying the target difference and the target no-difference”

February 21 @ 2:00 pm - 3:00 pm
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Free

Speaker: Prof Steven Julious, University of Sheffield Title: "Sample size considerations for the design clinical trials - quantifying the target difference and the target no-difference" Abstract: One of the most of the important steps in any clinical trial design is the calculation of the sample size calculation.  From this the study timelines and financial budgets are calculated.  A major driver in the sample size calculation size calculation is the target difference (for a superiority trial) or the target no-difference (for a non-inferiority…

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BSU Seminar: “Optimal Feature Selection using model-based Deep Reinforcement Learning”

February 26 @ 2:00 pm - 3:00 pm
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Free

Speaker: Dr Konstantina Pallas, Microsoft Title: "Optimal Feature Selection using model-based Deep Reinforcement Learning" Abstract: TBC  

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March 2019

Machine learning meets statistics: Guiding medicine into the future

March 25 @ 9:00 am - March 26 @ 5:00 pm
Clifford Allbutt Lecture Theatre, 307 Hills Road
Cambridge, CB2 0XY United Kingdom
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SOLD OUT

SOLD OUT Joint workshop, organised by The Alan Turing Institute and MRC Biostatistics Unit, University of Cambridge Traditional statistical analysis and machine learning have many things in common but usually follow paths that are quite different. For prediction, traditional statistical analysis usually begins with a theory and a model and fits the parameters of the model to the data; machine learning follows a more pragmatic approach, allowing the data more freedom to prescribe the model.  Machine learning often leads to…

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April 2019

BSU Seminar: “Building Representative Matched Samples with Multi-valued Treatments in Large Observational Studies”

April 11 @ 2:00 pm - 3:00 pm
Large Seminar Room, IPH, Institute of Public Health, Forvie Site
Cambridge, CB2 0SR United Kingdom
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Free

Speaker: Professor Jose Zubizarreta, Harvard University Title: "Building Representative Matched Samples with Multi-valued Treatments in Large Observational Studies" Abstract: In observational studies of causal effects, matching methods are widely used to approximate the ideal study that would be conducted under controlled experimentation. In this talk, I will discuss new matching methods that use tools from modern optimization to overcome five limitations of standard matching approaches. In particular, these new matching methods (i) directly obtain flexible forms of covariate balance, as specified before matching…

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