Application of machine learning methodologies on the UK biobank dataset to predict onset of depression
We aim to identify middle-aged adults who are at risk for future depression. Depression is a major cause of disability globally, with a peak of prevalence among middle-aged adults. Identifying a combination of factors that are most predictive of upcoming depressive episode in middle-aged individuals is crucial for developing prevention strategies. Previous work have shown the great potential of mahcine-learning techniques for similar goals. We expect that the analysis can be done in 6 months.