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Predicting generalized anxiety disorder among women using Shapley value.

Neesha Jothi1, Wahidah Husain1, Nur'Aini Abdul Rashid1

  • 1School of Computer Sciences, Universiti Sains Malaysia, 11800 Penang, Malaysia.

Journal of Infection and Public Health
|April 11, 2020
PubMed
Summary

This study introduces a novel data mining approach using Shapley values to predict generalized anxiety disorder (GAD) in women. Early identification of GAD can improve mental health awareness and encourage timely support seeking.

Keywords:
Data miningData mining in healthcareFeature selectionGeneralized anxiety disorderShapley value

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Area of Science:

  • Psychiatry and Data Science
  • Computational Mental Health

Background:

  • Mental illnesses, including anxiety disorders, are prevalent but often misunderstood.
  • Existing data mining research inadequately addresses specific conditions like generalized anxiety disorder (GAD).
  • There is a need for improved methods to identify GAD, particularly in women.

Purpose of the Study:

  • To develop and implement a novel data mining system for predicting GAD in women.
  • To apply Shapley value as a feature selection method within a data mining classifier.
  • To enhance the early detection of GAD for improved mental health outcomes.

Main Methods:

  • The study adapted the Knowledge Discovery in Databases (KDD) methodology.
  • Key phases included data acquisition, pre-processing, feature selection (Shapley value), classification, and evaluation.
  • A novel feature selection and data mining classifier system was implemented.

Main Results:

  • The proposed method successfully implements Shapley value for feature selection in GAD prediction.
  • The data mining approach facilitates the identification of potential GAD cases in women.
  • The system aims to improve the accuracy and efficiency of GAD detection.

Conclusions:

  • The developed data mining system offers a promising tool for identifying generalized anxiety disorder in women.
  • This research addresses a gap in data mining applications for specific mental health conditions.
  • The study aims to increase mental health awareness and empower women to seek necessary services.