This study explores the trends and patterns in suicide risk factors using data mining techniques. Medical records of 666 suicide attempters who were admitted to a teaching hospital from January 2004 to December 2006 were studied. Data mining techniques revealed hidden patterns for repeated and single attempters, as well as suicide precipitants and risk factors. The findings have implications for further research in suicide assessment and intervention.
|Title of host publication||Mental Health Informatics|
|Editors||Margaret Lech, Insu Song, Peter Yellowlees, Joachim Diederich|
|Publisher||Springer-Verlag London Ltd.|
|Number of pages||12|
|Publication status||Published - 2014|
|Name||Studies in Computational Intelligence|