Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8688863 | NeuroImage: Clinical | 2017 | 8 Pages |
Abstract
We observed that a machine learning algorithm accurately predicted epilepsy duration based on global metrics of network architecture derived from resting state fMRI. These findings suggest that network metrics have the potential to form the basis for statistical models that translate quantitative imaging data into patient-level markers of cognitive deterioration.
Keywords
Related Topics
Life Sciences
Neuroscience
Biological Psychiatry
Authors
Michael J. Paldino, Wei Zhang, Zili D. Chu, Farahnaz Golriz,