Prediction of suicidal ideation in shift workers compared to non-shift workers using machine learning techniques

Shift work can affect sleep and increase the risk of suicide. This study attempted to predict suicidal ideation according to shift work by using machine learning techniques. We analyzed a total of 43,095 data conducted by using the 10-year Korean National Health and Nutrition Examination Survey (KHA...

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Veröffentlicht in:	Journal of affective disorders 2022-06, Vol.307, p.125-132
Hauptverfasser:	Park, Hwanjin, Lee, Kounseok
Format:	Artikel
Sprache:	eng
Schlagworte:	Daytime workers Depression Humans Machine Learning Nutrition Surveys Quality of Life Risk Factors Shift workers Suicidal Ideation Suicide
Online-Zugang:	Volltext
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