Abstract #4555

Support vector machine prediction of clinical pain response using resting-state fMRI

Scott J. Peltier^1,2, Eric Ichesco³, Lynne Pauer⁴, Daniel J. Clauw³, and Richard E. Harris ³

¹Functional MRI Laboratory, University of Michigan, Ann Arbor, MI, United States, ²Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States, ³Anesthesiology, University of Michigan, Ann Arbor, MI, United States, ⁴Pfizer Inc., Groton, CT, United States

The mechanisms of chronic pain and its response to pharmacological treatment remains an open challenge. Multivariate pattern analysis can offer an alternative to standard analysis techniques. This study applies SVM classification in resting-state fMRI data to predict improvements in clinical pain after drug therapy.

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