Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models

This study identified key factors such as older age, lower education, divorce or widowhood, employment, physical methods, and socioeconomic issues as significant predictors of suicidal behavior outcomes. A combination of statistical models for feature selection and machine learning algorithms for prediction was used, with Random Forest showing the best performance. This approach highlights the potential of integrating statistical methods with machine learning to improve suicide risk prediction and intervention strategies.