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

Yaowarat Sirisathitkul, Putthiporn Thanathamathee, Saifon Aekwarangkoon

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


Bibliography


Sirisathitkul, Y., Thanathamathee, P., & Aekwarangkoon, S. (2019). Predictive apriori algorithm in youth suicide prevention by screening depressive symptoms from patient health questionnaire-9. TEM Journal, 8(4) 1449-1455. doi:10.18421/TEM84-49

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