Abstract
Mental health plays a significant role in the comprehensive growth and development of college students. It refers to the positive development of the mental state which determines their mental or physical potential. The mental health problems of college students increase day by day and become a crucial aspect for families, colleges, universities and society. In existing methods, issues occur due to large variations in the symptoms of mental illness which further results in more than one disease condition at the same time. This creates complexities in the accurate diagnosis of mental health. Based on the present situation of student's mental health, an early warning platform is developed for observing the effect of social media, bad emotions and other factors on the minds of college students. Subsequently, relevant treatment is provided to overcome the diseases caused by mental illness and to improve mental health. Mental health platforms are constructed to improve the health state of college or university students and protect them from psychological crisis. In this paper, a specific framework and module for testing and training schemes based on deep neural model for the analysis of mental state of college students is introduced. The corresponding experimental analysis is carried on the generated set of data for improved validation.
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