A Mental Disorder Prediction Model with the Ability of Deep Information Expression Using Convolution Neural Networks Technology

Pufang Huang,Tongguang Ni

doi:10.1155/2022/4664102

Abstract

The psychological health education work of all universities is currently facing the same problem, despite the rapidly expanding scale of universities and the ever-increasing demand for students: there are few teachers engaged in this field, who cannot meet the urgent needs of the majority of students. Because of their mental illness, university students are unable to complete their studies in a timely manner, affecting their own development. One after the other, such occurrences occur. This paper uses the common mental disorder identification of university students as an example and builds a mental disorder identification model based on CNN. The model has the ability to learn on its own, allowing it to diagnose psychological disorders in university students and provide support for college psychological counselling and the psychological health team. However, because China currently pays little attention to the psychological health of this population, it is necessary to investigate and analyse the psychological health of university students at this time.

Highlights

Many people are experiencing varying degrees of psychological barriers as a result of increasing pressure from all directions in society, family, and life
Family harmony, and happiness have all suffered as a result of psychological obstacles [1]. e psychological health education work of all universities is currently facing the same problem, despite the rapidly expanding scale of universities and the ever-increasing demand for students: there are few teachers engaged in this field, which cannot meet the urgent needs of the majority of students [2]. e severe shortage of full-time psychological counsellors in universities has become a major impediment to psychological health education and intervention
According to the analysis of the factors affecting the psychological health of contemporary university students, we can summarize it into 10 influencing factors: personal future pressure, social pressure, economic pressure, environmental adaptation pressure, study pressure, emotional pressure, parental expectation pressure, family influence pressure, professional emotional pressure, and interpersonal pressure

Summary

Introduction

Many people are experiencing varying degrees of psychological barriers as a result of increasing pressure from all directions in society, family, and life. We must take seriously the psychological health problems of university students, fully analyse and study the causes of university students’ mental problems, and understand the factors affecting psychological health. Is paper analyses the reasons affecting the psychological health of Chinese university students, expands the evaluation factors, collects the corresponding data, uses the convolution NN model to predict and analyse the psychological health of university students, and establishes a convolution NN forecasting model suitable for the identification of mental disorders, based on the current situation and characteristics of Chinese students. Universities only offer consultation and guidance in the field of psychological health education to university students through school psychological counselling teachers or hospital psychological experts. E model can detect university students’ psychological status and provide diagnosis results in real time, as well as providing support for psychological consultation and psychological health teams in universities In order to cope with psychological health demands in the future, researchers are looking into the internal law of numerous aspects affecting psychological health. is helps to generate new ideas for psychological health work. is paper developed a CNN-based [6] psychological disorder identification model. e error between the predicted outcomes and the measured value output by the ANN [7] is small after sample training, and the expected effect is well achieved. e model can detect university students’ psychological status and provide diagnosis results in real time, as well as providing support for psychological consultation and psychological health teams in universities

Related Work

Mental Disorder Prediction Based on CNN

Findings

Analysis and Discussion