- Wednesday, May 25th 2016 at 15:00 - 16:00 UK (Other timezones)
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The last few years has witnessed an explosion of the number and types of biological measures that can -and are- measured quantitatively and non-invasively in clinical populations. In most areas of medicine, this has led to biological tests that have revolutionised diagnosis and treatment allocation. However, this is not the case in psychiatry, which is now virtually the last area of medicine where diseases are still diagnosed based on symptoms and biological tests to assist treatment allocation remain to be developed. In this talk, I will present work from our group that aims to use neuroimaging data derived from large population-based cohorts as biomarkers that predict disease state and outcome in psychiatric disorders. I will also discuss recent initiatives for mapping the hetereogeneity underlying psychiatric disorders on the basis of mappings between biology and the behaviours that depend on that biology. This provides a method to understand variation in clinical cohorts at the level of individual participants, so that each individual subject can be placed within the population range and disease mechanisms can be studied independently from the diagnostic labels. The hope is that this will move the field beyond simple case-control comparisons and will ultimately lead to biologically based tests that improve outcomes for patients.
Andre Marquand is Assistant Professor at the Donders Institute, working in the Statistical Imaging Neuroscience group. He has a particular focus on machine learning techniques that aim to learn to detect patterns of statistical regularity in empirical data. These methods hold significant promise for decoding cognitive states and predicting clinically relevant variables in health and disease.
Video of the session: