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Exploring the prediction of emotional valence and pharmacologic effect across fMRI studies of antidepressants.

Version:
0.1

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Department:
Yale University
Role:
Data curator, Researcher, Creator

Contributors

Department:
Paediatrics
Role:
Principal Investigator (PI), Data curator, Supervisor
Publisher:
University of Oxford
Publication date:
2018
Version number:
0.1
DOI:
Keywords:
Documentation:
Data for: Exploring the prediction of emotional valence and pharmacologic effect across fMRI studies of antidepressants. Authors: Daniel Barron, Mehraveh Salehi, Michael Browning, Catherine J Harmer, R. Todd Constable, Eugene Duff DATA: 268 features (column) for 306 subjects (rows). There is a separate groupings file that associates each row with each subject, clinical group, and experimental task. CODE_Python: takes the 268 features and uses a GBM classifier to predict group association. ... Expand documentation
UUID:
uuid:32cfa004-3975-4fd4-bb26-3ae13f766226
Deposit date:
2018-08-28

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