Technology companies such as Google, Facebook and Apple have long been using deep learning technology (DLT) for big data analysis in order to predict how people search the internet, what news they are interested in, and who their potential friends are. In light of its superior ability to detect high orders of complexity and abstraction in the data, DLT is also becoming the focus of increasing attention in the brain sciences. This presentation will provide an overview of DLT and its potential applications to the investigation of brain-based disorders. In the first part, I will outline the key concepts of DLT including its main strengths and limitations. In the second part, I will introduce Neurofind - a user-friendly web-based tool which uses deep learning technology to quantify neuroanatomical abnormalities from structural Magnetic Resonance Imaging scans. The tool could help researchers and clinicians assess the presence of a psychiatric or neurological disorder, monitor its progression over time and optimise treatment in individual patients.
