Predicting Depression
- 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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