School of Medical Information Engineering, Gannan Medical University, Ganzhou 341000, China.
First Affiliated Hospital of Gannan Medical University, Ganzhou 341000, China.
Comput Intell Neurosci. 2022 Jul 13;2022:7119994. doi: 10.1155/2022/7119994. eCollection 2022.
The mental health problems of college students have attracted the attention of all sectors of society. In order to keep college students in a good mental state and effectively analyze their mental health, an intelligent evaluation system of college students' mental health based on big data is designed. Based on big data technology, this article constructs an intelligent evaluation system for college students' mental health, which is divided into six layers, namely, application layer, decision layer, interface layer, analysis layer, data layer, and basic layer. Then, the mental health data of college students were collected based on C/S architecture. On the basis of extracting and integrating data characteristics, six evaluation indexes of personality, will, emotion, depression, fear, and psychosis were screened, and then, the intelligent evaluation was completed according to the weight of indexes. On the basis of the preliminary verification of the performance of the system in this article, according to the comparative experimental results, the mental health data acquisition time of the system is less, the accuracy of data feature extraction and the recall rate of evaluation results are higher.
大学生心理健康问题已引起社会各界的关注。为了使大学生保持良好的心理状态，并有效分析他们的心理健康状况，设计了一个基于大数据的大学生心理健康智能评价系统。本文基于大数据技术构建了大学生心理健康智能评价系统，该系统分为应用层、决策层、接口层、分析层、数据层和基础层六层。然后，基于 C/S 架构收集大学生心理健康数据。在提取和整合数据特征的基础上，筛选出人格、意志、情绪、抑郁、恐惧和精神病这六个评价指标，然后根据指标权重完成智能评价。在初步验证本文系统性能的基础上，根据对比实验结果，该系统的心理健康数据采集时间更短，数据特征提取的准确性和评价结果的召回率更高。
