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Scientific Lectures //

Computational Psychiatry: Towards Clinical Applications of Machine Learning

Matthew Brown, Ph.D.- Research Associate, Department of Psychiatry, University of Alberta

Presented: June 25, 2015 

ABSTRACT: Machine learning offers potential for improved diagnostic accuracy, early detection, and prediction of patient response to treatment in psychiatry. Encouraging early results in this area used small sample sizes (eg: n=20). Moving toward larger samples is an important next step but introduces challenges in terms of patient heterogeneity and data collection from multiple sites. I will discuss our work applying machine learning to MRI and fMRI brain images, as well as clinical data, in multiple psychiatric disorders, using medium to large samples (n=75 up to n=1000).

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