Exploring Factors Influencing Suicidal Ideation in Workers with Mental Disabilities Using Machine Learning Ensemble Techniques

Suicide is a critical public health issue globally, with South Korea exhibiting the leading suicide rate within OECD nations. This study aims to identify factors influencing suicidal ideation among workers with mental disabilities using machine learning ensemble techniques, specifically Bagging and Boosting. Data from the 2022 Ministry of Health and Welfare's

Authors

Publication Details

Journal
Universal Journal of Public Health
Published
2024-10-01
DOI
https://doi.org/10.13189/ujph.2024.120522
Primary Topic
Education, Safety, and Science Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring Factors Influencing Suicidal Ideation in Workers with Mental Disabilities Using Machine Learning Ensemble Techniques

Haewon Byeon
Universal Journal of Public Health
Education, Safety, and Science Studies
article

Exploring Factors Influencing Suicidal Ideation in Workers with Mental Disabilities Using Machine Learning Ensemble Techniques

Haewon Byeon
article en

Abstract

Suicide is a critical public health issue globally, with South Korea exhibiting the leading suicide rate within OECD nations. This study aims to identify factors influencing suicidal ideation among workers with mental disabilities using machine learning ensemble techniques, specifically Bagging and Boosting. Data from the 2022 Ministry of Health and Welfare's

Universal Journal of Public HealthVol. 12(5)
Reduced inequalities
Openalex Percentile: Top 79%
Education, Safety, and Science Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Exploring Factors Influencing Suicidal Ideation in Workers with Mental Disabilities Using Machine Learning Ensemble Techniques — Haewon Byeon · Universal Journal of Public Health (2024) | TGRS Research Map | TGRS