Abstract
Progress in predicting treatment outcomes – despite extensive research – has been disappointing as standard analyses do not reveal predictors of any relevance. The past two decades has seen rapid development of Machine Learning (ML) methods for improving the prediction of treatment outcomes. In this project, student will analyse large observational data and apply ML methods to develop models for identifying predictors, which could be used to predict likely size of benefit for each patient before treatment. This is one of the first studies to apply ML to predict outcomes of complex interventions in psychiatric care.
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