Optimizing Suicide Risk Prediction in Korea: A Comparison of Model Performance Using Resampling Methods and Machine Learning Algorithms

• 발행기관: 대한신경정신의학회
• 저자명: Eunji Lim Bong-Jo Kim Boseok Cha So-Jin Lee Jae-Won Choi Nuree Kang Soyoung Park Sung Hyo Seo Dongyun Lee
• 간행물 정보: 『Psychiatry Investigation』제22권 제11호, 1309~1318쪽, 전체 10쪽
• 주제분류: 의약학 > 정신과학
• 파일형태: PDF
• 발행일자: 2025.11.30

국문 초록

Objective: Machine learning (ML) can assist in predicting suicide risk and identifying associated risk factors. Various resampling methods and algorithms must be applied to develop an ML prediction model with better performance. In this study, we developed an optimal Korean suicide prediction model by applying five ML algorithms, unsampled data, and two resampling methods. Methods: In this study, data from the Korea National Health and Nutrition Examination Survey for 2017, 2019, and 2021 were integrated and analyzed to predict suicidal ideation in subjects aged ≥19 years. Logistic regression, random forest (RF), k-nearest neighbor, gradient boosting, and adaptive boosting were used as ML algorithms. Undersampling and oversampling are used as resampling methods to solve data imbalance problems. Results: Among the study participants, 16,947 (95.14%) and 866 (4.86%) belonged to the control and suicidal ideation groups, respectively. Among the 15 ML models, the RF model exhibited excellent performance (sensitivity=0.781, area under the curve=0.870) in an algorithm trained with undersampled data. Conclusion: Developing an optimized Korean suicide prediction model through additional validation based on the ML model developed in this study will help predict suicide risk factors caused by the interaction of individual, social, and environmental factors.

목차

INTRODUCTION

METHODS

RESULTS

DISCUSSION

Supplementary Materials

Availability of Data and Material

Conflicts of Interest

Author Contributions

ORCID iDs

Funding Statement

Acknowledgments

REFERENCES

키워드

Machine learning Random forest Undersampling Oversampling Suicidal ideation KNHANES