Potential suicide risk among the college student population: machine learning approaches for identifying predictors and different students' risk profiles.

Machine learning techniques could hold promise for assessing suicide risk in college students, potentially leading to the development of more effective prevention programs. These programs should address both risk and protective factors and be tailored to students' needs and to the different categories of risk.