Log in to save to my catalogue
Log in to save to my catalogue

Classification of first-episode psychosis in a large cohort of patients using support vector machine...

| Ask | Become a Library member

Classification of first-episode psychosis in a large cohort of patients using support vector machine...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1826646255

Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques

About this item

Full title

Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques

Author / Creator

The GET UP Group , GET UP Group , Squarcina, Letizia , Castellani, Umberto , Bellani, Marcella , Perlini, Cinzia , Lasalvia, Antonio , Dusi, Nicola , Bonetto, Chiara , Cristofalo, Doriana , Tosato, Sarah , Rambaldelli, Gianluca , Alessandrini, Franco , Zoccatelli, Giada , Pozzi-Mucelli, Roberto , Lamonaca, Dario , Ceccato, Enrico , Pileggi, Francesca , Mazzi, Fausto , Santonastaso, Paolo , Ruggeri, Mirella and Brambilla, Paolo

Publisher

United States: Elsevier Inc

Journal title

NeuroImage (Orlando, Fla.), 2017-01, Vol.145 (Pt B), p.238-245

Language

English

Formats

Articles

Publication information

Publisher

United States: Elsevier Inc

Subjects

More information

Scope and Contents

Contents

First episode psychosis (FEP) patients are of particular interest for neuroimaging investigations because of the absence of confounding effects due to medications and chronicity. Nonetheless, imaging data are prone to heterogeneity because for example of age, gender or parameter setting differences. With this work, we wanted to take into account po...

Alternative Titles

Full title

Classification of first-episode psychosis in a large cohort of patients using support vector machine and multiple kernel learning techniques

Authors, Artists and Contributors

Author / Creator

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_miscellaneous_1826646255

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1826646255

Other Identifiers

ISSN

1053-8119

E-ISSN

1095-9572

DOI

10.1016/j.neuroimage.2015.12.007

How to access this item

Log in as a Library member

Full text available

About resource

View in old catalogue

Connecting people and collections