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A Development of Adolescent Depression Screening Using Naïve Bayes Classifier Algorithm

  • Samuel Garbo
  • Ha-Yeong Kim
  • Syntia Widyayuningtias Putri
  • Ermal Elbasani
  • Hye-Sun Ahn
  • Jeong-Dong KimEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 536)

Abstract

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.

Keywords

Depression Adolescent depression screening Naïve Bayes algorithm Beck depression inventor 

Notes

Acknowledgments

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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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Samuel Garbo
    • 1
  • Ha-Yeong Kim
    • 1
  • Syntia Widyayuningtias Putri
    • 1
  • Ermal Elbasani
    • 1
  • Hye-Sun Ahn
    • 2
  • Jeong-Dong Kim
    • 1
    Email author
  1. 1.School of Computer Science and EngineeringSun Moon UniversityAsan-siKorea
  2. 2.Graduate School IT Policy and ManagementSoongsil UniversitySeoulKorea

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