Sparse deep neural networks on imaging genetics for schizophrenia case–control classification
Sparse deep neural networks on imaging genetics for schizophrenia case–control classification
About this item
Full title
Author / Creator
Publisher
Hoboken, USA: John Wiley & Sons, Inc
Journal title
Language
English
Formats
Publication information
Publisher
Hoboken, USA: John Wiley & Sons, Inc
Subjects
More information
Scope and Contents
Contents
Deep learning methods hold strong promise for identifying biomarkers for clinical application. However, current approaches for psychiatric classification or prediction do not allow direct interpretation of original features. In the present study, we introduce a sparse deep neural network (DNN) approach to identify sparse and interpretable features...
Alternative Titles
Full title
Sparse deep neural networks on imaging genetics for schizophrenia case–control classification
Authors, Artists and Contributors
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Primary Identifiers
Record Identifier
TN_cdi_swepub_primary_oai_swepub_ki_se_463544
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_swepub_primary_oai_swepub_ki_se_463544
Other Identifiers
ISSN
1065-9471,1097-0193
E-ISSN
1097-0193
DOI
10.1002/hbm.25387
