Journal of Korea Artificial Intelligence Association

Korea Distribution Science Association (한국유통과학회)
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Prediction of Depression from Machine Learning Data

머신러닝 데이터의 우울증에 대한 예측

  • Jeong Hee KIM (Bigdata medical convergence, Bio-convergence, Eulji University) ;
  • Kyung-A KIM (Bigdata medical convergence, Bio-convergence, Eulji University)
  • Received : 2023.04.19
  • Accepted : 2023.06.29
  • Published : 2023.06.30
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Abstract

The primary objective of this research is to utilize machine learning models to analyze factors tailored to each dataset for predicting mental health conditions. The study aims to develop appropriate models based on specific datasets, with the goal of accurately predicting mental health states through the analysis of distinct factors present in each dataset. This approach seeks to design more effective strategies for the prevention and intervention of depression, enhancing the quality of mental health services by providing personalized services tailored to individual circumstances. Overall, the research endeavors to advance the development of personalized mental health prediction models through data-driven factor analysis, contributing to the improvement of mental health services on an individualized basis.

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References

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