TEM Journal, Volume 8, Issue 4, Pages 1449-1455 , 01/11/2019
Predictive apriori algorithm in youth suicide prevention by screening depressive symptoms from patient health questionnaire-9
Abstract
This study employed the Predictive A priori algorithm in identifying significant questions of Patient Health Questionnaire-9 (PHQ-9) for suicide tendency prediction by using PHQ-9 and suicidal screening form (8Q). The random forest was applied to calculate the classification accuracy of PHQ-9 and 3 feature selection algorithms were applied to determine the attribute importance. The Predictive Apriori algorithm was applied to find the meaningful association rules. The classification accuracy of PHQ-9 is 92.12% and item no. 1 and no. 9 of PHQ-9 are less important. The significant risk factors associated with suicidal ideation are Item no. 2, no. 4, and no. 5.
Document Type
Article
Source Type
Journal
Keywords
DepressionFeature selectionPredictive apriori algorithmRandom forestSuicidal risk
ASJC Subject Area
Business, Management and Accounting : Management of Technology and InnovationBusiness, Management and Accounting : Strategy and ManagementComputer Science : Computer Science (miscellaneous)Computer Science : Information SystemsDecision Sciences : Information Systems and ManagementSocial Sciences : Education
Funding Agency
Walailak University