An evaluation model for college students' mental health based on machine learning algorithm
by Qiaoying Ming
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 28, No. 1, 2025

Abstract: Owing to the traditional beliefs, people tend to be hesitant and reserved in expressing themselves. To achieve accurate assessment of college students' mental health problems, a CNN-BiLSTM mental health assessment algorithm based on metaphorical attention mechanism is proposed. CNN-BiLSTM text processing module and metaphorical attention mechanism are used to improve the evaluation effect. The results show that compared with Text-CNN, BiLSTM+multi-layer RNN and BiLSTM+Attention, the recall rate and F1-value of the proposed algorithm are increased by 6.52% and 4.04%, respectively, and the prediction effect is best. After the elimination of RNN_MIP, metaphorical attention mechanism and BiLSTM, F1-value decreases by 2.33%, 8.72% and 5.7%, respectively, and the decrease is obvious.

Online publication date: Mon, 02-Dec-2024

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