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Due to absence of good and high prevalence rate of the comprehensive method of automatic assessment, the current mental health assessment is still subject to manual answer questionnaires. The main drawback of this is that the detection of mental health issues of contemporary college students through the manual answer questionnaire is not satisfactory. Mental health problems of the students cannot be properly detected, and as a result, they remain deprived of timely psychological counseling and treatment. At the same time, in order to improve the accuracy of automatic selection of mental health and the popularity of this solution, this study first presents a detailed analysis of the possible mental health problems encountered by contemporary college students. A radial basis function (radial basis function, RBF) neural network application in the automatic selection of mental health status and comparative verification. The results proved the higher accuracy and warning of the RBF nervous system in comparison to the mental health of contemporary college students. The research further investigates the dependence of the psychological problems and solutions of contemporary college students on data analysis. It can be rightly said that the study is of great importance due to its provision of new research direction and relevant countermeasures for the psychological problems of college students.