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Vol.8, No.4, November 2019. ISSN: 2217-8309 eISSN: 2217-8333
TEM Journal
TECHNOLOGY, EDUCATION, MANAGEMENT, INFORMATICS Association for Information Communication Technology Education and Science |
Predictive Apriori Algorithm in Youth Suicide Prevention by Screening Depressive Symptoms from Patient Health Questionnaire-9
Yaowarat Sirisathitkul, Putthiporn Thanathamathee, Saifon Aekwarangkoon
© 2019 Yaowarat Sirisathitkul, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)
Citation Information: TEM Journal. Volume 8, Issue 4, Pages 1449-1455, ISSN 2217-8309, DOI: 10.18421/TEM84-49, November 2019.
Received: 23 August 2019. Revised: 31 October 2019.
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.
Keywords – Depression, Feature selection, Predictive Apriori algorithm, Random forest, Suicidal risk. |
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