Psychological disorders are the primary health issue affecting college students in the new era,and there is currently no early predictive tool available for screening psychological disorders among college students.The rapid development of artificial intelligence technology has provided new ideas and methods for research in the field of mental health.This study is based on sample data of students from different levels of universities in Zhejiang province.By constructing a CNN-LSTM deep learning model to identify risk factors for psychological disorders in college students,and comparing CNN-LSTM with models constructed by SVM,BP,and CNN based on target predictive variables,multiple predictive performance evaluation indicators such as AUC are compared.The final validation of the constructed CNN-LSTM model shows the best performance in predicting psychological disorders among college students,and has practical application potential for screening psychological disorders among college students.
关键词
心理障碍预测/深度学习/大学生/CNN/LSTM
Key words
prediction of psychological disorders/deep learning/college students/CNN/LSTM
维普
万方数据