@article{ref1,
title="Predictive apriori algorithm in youth suicide prevention by screening depressive symptoms from patient health questionnaire-9",
journal="TEM Journal",
year="2019",
author="Sirisathitkul, Y. and Thanathamathee, P. and Aekwarangkoon, S.",
volume="8",
number="4",
pages="1449-1455",
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. © 2019 Yaowarat Sirisathitkul, Putthiporn Thanathamathee, Saifon Aekwarangkoon.<p /><p>Language: en</p>",
language="en",
issn="2217-8309",
doi="10.18421/TEM84-49",
url="http://dx.doi.org/10.18421/TEM84-49"
}