| Paper: | PS-1B.14 |
| Session: | Poster Session 1B |
| Location: | Symphony/Overture |
| Session Time: | Thursday, September 6, 18:45 - 20:45 |
| Presentation Time: | Thursday, September 6, 18:45 - 20:45 |
| Presentation: |
Poster
|
| Publication: |
2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania |
| Paper Title: |
Deep Learning Classification Study of First-Episode Treatment-Naïve Schizophrenia Using Brain Cortical Area and Cognitive Features |
| Manuscript: |
Click here to view manuscript |
| DOI: |
https://doi.org/10.32470/CCN.2018.1187-0 |
| Authors: |
Yinfei Li, Tao Li, West China Hospital, China |
| Abstract: |
Deep learning neural network was for the first time used to discriminate schizophrenia patients from healthy controls. Neuroimaging and coginitive data were accquired as featres. Re-sampling was repeated 100 times and emsemble models were applied. The result show that the classification accuracy is satisfactorily high and robust. And the classification weights show that brain surface area and multiple domains of coginition were of high discriminate value in the disease. |
