A Development of Adolescent Depression Screening Using Naïve Bayes Classifier Algorithm
Adolescent depression is a prevalent cause of illness and disability for teenagers. Getting treatment at the earliest sign helps prevent depression from worsening. Depression symptoms can be difficult to tell apart from ups and downs that are part of adolescence thus not being able to contact a professional at the earliest sign. Smartphone applications, are easily available to users of all ages. With an Android application we propose an easily accessible depression screening method for adolescents. Using a widely used depression scale and Naïve Bayes classifier, we compare previous data to the current situation of the user to produce an estimation of the user’s situation.
KeywordsDepression Adolescent depression screening Naïve Bayes algorithm Beck depression inventor
This work was supported by 2018 LINC+ project of Sun Moon University and by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2019R1F1A1058394).
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