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dc.contributor.authorCaon, F
dc.contributor.authorMeneghel, G
dc.contributor.authorZaghi, P
dc.contributor.authorDe Leo, D
dc.date.accessioned2017-05-03T14:16:34Z
dc.date.available2017-05-03T14:16:34Z
dc.date.issued2002
dc.date.modified2010-09-24T06:48:53Z
dc.identifier.issn1381-1118
dc.identifier.doi10.1080/13811110214139
dc.identifier.urihttp://hdl.handle.net/10072/6572
dc.description.abstractSuicide is a leading cause of death internationally. Prediction of the phenomenon has proved to be extremely difficult and results in this area have been modest. The objective of this pilot study was to assess the applicability of the Neural Network statistical procedure to suicidal data. The predictive ability of three statistical techniques (Logistic Regression, Discriminatory Analysis and Neural Networks) were compared in the ability to distinguish between suicides and attempts on the basis of a variety of variables. Although the Neural Network model expresses its full potential with large numbers, it has proved to be effective even in our limited sample. This suggests that neural networks may exhibit superior predictive capacity when the data set is enlarged. This technique may prove to be a useful additional tool in the field of suicide prediction and prevention.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.language.isoeng
dc.publisherBrunner-Routledge, Taylor & Francis Group
dc.publisher.placeUnited Kingdom
dc.relation.ispartofpagefrom285
dc.relation.ispartofpageto289
dc.relation.ispartofjournalArchives of Suicide Research
dc.relation.ispartofvolume6
dc.subject.fieldofresearchPsychology
dc.subject.fieldofresearchcode1701
dc.titleApplicability of neural networks to suicidological research: A pilot study
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.date.issued2002
gro.hasfulltextNo Full Text
gro.griffith.authorDe Leo, Diego


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