Article: Machine learning model-based monitoring of mental health status of college students Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.2 pp.36 - 50 Abstract: This article proposes a method for monitoring the mental health status of college students based on machine learning models. By integrating multidimensional data such as psychological assessment questionnaires and daily behaviour data, and using machine learning techniques such as support vector machine, random forests, and deep learning algorithms, a prediction model that can efficiently identify the mental health status of college students is constructed. This model improves the quality of data and the accuracy of model predictions through steps such as feature engineering and data preprocessing. This article used real datasets from multiple universities for experimental testing, and the results showed that the method performed well in multiple evaluation indicators such as accuracy, recall, and F1 score, demonstrating strong practicality and promotional value. Inderscience Publishers - linking academia, business and industry through research

Title: Machine learning model-based monitoring of mental health status of college students

Authors: Baoqin Gong; Ninghua Huang

Addresses: School of Marxism, Xi'an Siyuan University, Xi'an 710038, China ' School of Marxism, Changsha University of Science and Technology, Changsha 410011, China

Abstract: This article proposes a method for monitoring the mental health status of college students based on machine learning models. By integrating multidimensional data such as psychological assessment questionnaires and daily behaviour data, and using machine learning techniques such as support vector machine, random forests, and deep learning algorithms, a prediction model that can efficiently identify the mental health status of college students is constructed. This model improves the quality of data and the accuracy of model predictions through steps such as feature engineering and data preprocessing. This article used real datasets from multiple universities for experimental testing, and the results showed that the method performed well in multiple evaluation indicators such as accuracy, recall, and F1 score, demonstrating strong practicality and promotional value.

Keywords: deep learning; machine learning; mental health; college student psychology.

DOI: 10.1504/IJICT.2025.144053

International Journal of Information and Communication Technology, 2025 Vol.26 No.2, pp.36 - 50

Received: 08 Dec 2024
Accepted: 16 Dec 2024
Published online: 22 Jan 2025 *

Title: Machine learning model-based monitoring of mental health status of college students

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