Identifying suicidal young adults

Barry Horwitz ()
Additional contact information
Barry Horwitz: National Institutes of Health

Nature Human Behaviour, 2017, vol. 1, issue 12, 860-861

Abstract: Functional brain-imaging methods provide rich datasets that can be exploited by machine-learning techniques to help assess psychiatric disorders. A recent study uses this approach to identify patients with suicidal thoughts, and to distinguish those who have attempted suicide from those who have not.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41562-017-0239-6 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nathum:v:1:y:2017:i:12:d:10.1038_s41562-017-0239-6

Ordering information: This journal article can be ordered from
https://www.nature.com/nathumbehav/

DOI: 10.1038/s41562-017-0239-6

Access Statistics for this article

Nature Human Behaviour is currently edited by Stavroula Kousta

More articles in Nature Human Behaviour from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().