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Abstract #4180

Automated classification of ICA networks from resting state fMRI using Machine Learning framework

Ashish Anil Rao 1 , Hima Patel 1 , Ek Tsoon Tan 2 , Rakesh Mullick 1 , and Suresh Emmanuel Joel 1

1 General Electric Global Research, Bangalore, Karnataka, India, 2 General Electric Global Research, New York, United States

Automated classification of ICA derived components in to components of neuronal origin and components of noise origin will be very useful. Several attempts with modest results have been reported previously. Recently a method for classifcation of ICA derived from high resolution, long duration multiband scans has been reported. Here we present accurate automated classifier at a single subject single run level for the widely used conventional resting state fMRI.

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