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The Mining Method of Ideological and Political Elements in University Public Mental Health Courses Based on Artificial Intelligence Technology

Artificial intelligence technology has become an important part of the development of Internet technology. Artificial intelligence technology can help colleges and universities optimize the network ideological and political teaching system. Artificial intelligence technology provides more accurate d...

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Detalles Bibliográficos
Autores principales: Li, Fangfang, Gu, Le, Xu, Hongchao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9451957/
https://www.ncbi.nlm.nih.gov/pubmed/36089948
http://dx.doi.org/10.1155/2022/2829974
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author Li, Fangfang
Gu, Le
Xu, Hongchao
author_facet Li, Fangfang
Gu, Le
Xu, Hongchao
author_sort Li, Fangfang
collection PubMed
description Artificial intelligence technology has become an important part of the development of Internet technology. Artificial intelligence technology can help colleges and universities optimize the network ideological and political teaching system. Artificial intelligence technology provides more accurate data resources and rich and reliable educational technology means for online public mental health education in colleges and universities. This paper comprehensively uses a variety of methods such as qualitative and quantitative analysis, case and empirical analysis, literature analysis, and artificial intelligence technology. Artificial intelligence technology has been closely integrated with online public mental health education in colleges and universities. The model systematically analyzes the optimization methods of artificial intelligence technology methods for the online public mental health education system in colleges and universities, and constructs an innovation system for online public mental health education in colleges and universities. Based on the comprehensive analysis of artificial intelligence and public health in colleges and universities, this paper further proposes the application of artificial intelligence technology in online public mental health education in colleges and universities. On this basis, the model conducts an in-depth analysis of artificial intelligence technology and the online public mental health innovation system. The model supports the development of ideological and political teaching in colleges and universities through various forms such as idea innovation, path innovation, carrier innovation, and mechanism innovation.
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spelling pubmed-94519572022-09-08 The Mining Method of Ideological and Political Elements in University Public Mental Health Courses Based on Artificial Intelligence Technology Li, Fangfang Gu, Le Xu, Hongchao J Environ Public Health Research Article Artificial intelligence technology has become an important part of the development of Internet technology. Artificial intelligence technology can help colleges and universities optimize the network ideological and political teaching system. Artificial intelligence technology provides more accurate data resources and rich and reliable educational technology means for online public mental health education in colleges and universities. This paper comprehensively uses a variety of methods such as qualitative and quantitative analysis, case and empirical analysis, literature analysis, and artificial intelligence technology. Artificial intelligence technology has been closely integrated with online public mental health education in colleges and universities. The model systematically analyzes the optimization methods of artificial intelligence technology methods for the online public mental health education system in colleges and universities, and constructs an innovation system for online public mental health education in colleges and universities. Based on the comprehensive analysis of artificial intelligence and public health in colleges and universities, this paper further proposes the application of artificial intelligence technology in online public mental health education in colleges and universities. On this basis, the model conducts an in-depth analysis of artificial intelligence technology and the online public mental health innovation system. The model supports the development of ideological and political teaching in colleges and universities through various forms such as idea innovation, path innovation, carrier innovation, and mechanism innovation. Hindawi 2022-08-31 /pmc/articles/PMC9451957/ /pubmed/36089948 http://dx.doi.org/10.1155/2022/2829974 Text en Copyright © 2022 Fangfang Li et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Fangfang
Gu, Le
Xu, Hongchao
The Mining Method of Ideological and Political Elements in University Public Mental Health Courses Based on Artificial Intelligence Technology
title The Mining Method of Ideological and Political Elements in University Public Mental Health Courses Based on Artificial Intelligence Technology
title_full The Mining Method of Ideological and Political Elements in University Public Mental Health Courses Based on Artificial Intelligence Technology
title_fullStr The Mining Method of Ideological and Political Elements in University Public Mental Health Courses Based on Artificial Intelligence Technology
title_full_unstemmed The Mining Method of Ideological and Political Elements in University Public Mental Health Courses Based on Artificial Intelligence Technology
title_short The Mining Method of Ideological and Political Elements in University Public Mental Health Courses Based on Artificial Intelligence Technology
title_sort mining method of ideological and political elements in university public mental health courses based on artificial intelligence technology
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9451957/
https://www.ncbi.nlm.nih.gov/pubmed/36089948
http://dx.doi.org/10.1155/2022/2829974
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