The Emerging Field of Predictive Analytics in Neuroimaging: Applications, Challenges and Perspectives

Chairs: Tim Hahn / Martin Walter

Venue: lecture room 30

While our knowledge regarding the biological bases of psychiatric disorders has expanded massively in the last two decades, none of these findings have yet been translated into concrete clinical applications. One reason for this is that commonly conducted statistical analyses – while allowing for inference on the group level – do not enable predictions on the level of the individual. Against this background, methods from Predictive Analytics and multivariate pattern recognition have recently gained increasing attention, especially in the area of neuroimaging. The symposium provides an overview of the most recent developments in the emerging field of Predictive Analytics in Neuroimaging, focusing on methods and techniques for functional resting-state Magnetic Resonance Imaging (rs-fMRI) data. Specifically, we will outline current clinical applications, techniques for real-time data analysis as well as domain-knowledge-based and automated feature engineering for rs-fMRI data. Finally, we will suggest specific guidelines for the implementation of Big Data approaches and pipeline standardization in multi-center research.

Tim Hahn
, University of Frankfurt am Main

Susan Whitefield-Gabrieli, Massachusetts Institute of Technology

Jonas Richiardi, FINDlab at Stanford University and LabNIC at the University of Geneva

Joseph Kambeitz, LMU Munich

Cameron Craddock, Child Mind Institute, New York

Presentation of the winning team of the Predictive Analytics in Mental Health Competition