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Assessing the role of artificial intelligence in the mental healthcare of teachers and students

The integration of artificial intelligence (AI)-grounded procedures and the Internet of Things (IoT) is very important in the advancement of smart and intelligent paradigms. These techniques can be applied very efficiently for the development of various sectors, including the solution of mental heal...

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Detalles Bibliográficos
Autores principales: Lei, Ling, Li, Junfeng, Li, Wenrui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072038/
https://www.ncbi.nlm.nih.gov/pubmed/37362257
http://dx.doi.org/10.1007/s00500-023-08072-5
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author Lei, Ling
Li, Junfeng
Li, Wenrui
author_facet Lei, Ling
Li, Junfeng
Li, Wenrui
author_sort Lei, Ling
collection PubMed
description The integration of artificial intelligence (AI)-grounded procedures and the Internet of Things (IoT) is very important in the advancement of smart and intelligent paradigms. These techniques can be applied very efficiently for the development of various sectors, including the solution of mental health issues among students, especially in sports education. The proposed article is a summary and analysis of existing intelligent approaches employed to safeguard against numerous mental health issues during the academic journey of a learner. With the utilization of smart methodologies, it is very feasible to compute the stress or depression level of a student and improve academic performance and skills. With innovative technologies, it is possible to accurately analyze behavioral features and recognize any unwanted pattern for the timely detection of mental health issues. To assist the learners in becoming responsible citizens, it is very efficient to utilize AI for the improvement of their psychological quality and mental performance by reducing anxiety and depression levels. Smart methods can be applied for the recognition of personnel in educational sectors who are facing difficulties in performing their duties and can be motivated to enhance their mental level. The investigation then gathered several significant qualities from the literature already in the field and chose the most prevalent ones. The analytical hierarchy process (AHP) is then used to execute the weighting of these attributes. The Multi-Objective Optimization on the Basis of Research Analysis (MOORA) approach was used to rank the options.
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spelling pubmed-100720382023-04-04 Assessing the role of artificial intelligence in the mental healthcare of teachers and students Lei, Ling Li, Junfeng Li, Wenrui Soft comput Focus The integration of artificial intelligence (AI)-grounded procedures and the Internet of Things (IoT) is very important in the advancement of smart and intelligent paradigms. These techniques can be applied very efficiently for the development of various sectors, including the solution of mental health issues among students, especially in sports education. The proposed article is a summary and analysis of existing intelligent approaches employed to safeguard against numerous mental health issues during the academic journey of a learner. With the utilization of smart methodologies, it is very feasible to compute the stress or depression level of a student and improve academic performance and skills. With innovative technologies, it is possible to accurately analyze behavioral features and recognize any unwanted pattern for the timely detection of mental health issues. To assist the learners in becoming responsible citizens, it is very efficient to utilize AI for the improvement of their psychological quality and mental performance by reducing anxiety and depression levels. Smart methods can be applied for the recognition of personnel in educational sectors who are facing difficulties in performing their duties and can be motivated to enhance their mental level. The investigation then gathered several significant qualities from the literature already in the field and chose the most prevalent ones. The analytical hierarchy process (AHP) is then used to execute the weighting of these attributes. The Multi-Objective Optimization on the Basis of Research Analysis (MOORA) approach was used to rank the options. Springer Berlin Heidelberg 2023-04-04 /pmc/articles/PMC10072038/ /pubmed/37362257 http://dx.doi.org/10.1007/s00500-023-08072-5 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Focus
Lei, Ling
Li, Junfeng
Li, Wenrui
Assessing the role of artificial intelligence in the mental healthcare of teachers and students
title Assessing the role of artificial intelligence in the mental healthcare of teachers and students
title_full Assessing the role of artificial intelligence in the mental healthcare of teachers and students
title_fullStr Assessing the role of artificial intelligence in the mental healthcare of teachers and students
title_full_unstemmed Assessing the role of artificial intelligence in the mental healthcare of teachers and students
title_short Assessing the role of artificial intelligence in the mental healthcare of teachers and students
title_sort assessing the role of artificial intelligence in the mental healthcare of teachers and students
topic Focus
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072038/
https://www.ncbi.nlm.nih.gov/pubmed/37362257
http://dx.doi.org/10.1007/s00500-023-08072-5
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