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Predicting Depression

  • Writer: Sara Kimmich
    Sara Kimmich
  • Sep 11, 2017
  • 1 min read

Description: We aim to build a regressor from MRI data that enables prediction of a depressive phenotype (as measured by NEO, HADS, BDI, etc). The base plan is to derive a connectome from resting-state fMRI data from the MPI-Leipzig Mind-Brain-Body dataset, then build a cognitive-based predictive model (CPM) to predict depressive phenotypes. The accuracy of our model will be tested using cross-validation

Team: Technology is Magic

Contact information: Lead email: sallyeguthrie@gmail.com

- @sguthrie

- @samhitamurthy

- @amnaahmalik55

- @isha


 
 
 

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