Family-wise automatic classification in schizophrenia

R.C.W. Mandl, R.M. Brouwer, W. Cahn, R.S. Kahn, H.E. Hulshoff Pol

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

Automatic classification of individuals at increased risk for schizophrenia can become an important screening method that allows for early intervention based on disease markers, if proven to be sufficiently accurate. Conventional classification methods typically consider information from single subjects, thereby ignoring (heritable) features of the person's relatives. In this paper we show that the inclusion of these features can lead to an increase in classification accuracy from 0.54 to 0.72 using a support vector machine model. This inclusion of contextual information is especially useful in diseases where the classification features carry a heritable component. © 2013 Elsevier B.V.
Original languageEnglish
Pages (from-to)108-111
JournalSchizophrenia Research
Volume149
Issue number1-3
DOIs
Publication statusPublished - Sep 2013
Externally publishedYes

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