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AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients
The COVID-19 pandemic has adverse consequences on human psychology and behavior long after initial recovery from the virus. These COVID-19 health sequelae, if undetected and left untreated, may lead to more enduring mental health problems, and put vulnerable individuals at risk of developing more se...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751545/ https://www.ncbi.nlm.nih.gov/pubmed/35027902 http://dx.doi.org/10.3389/fpsyg.2021.782866 |
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author | Ćosić, Krešimir Popović, Siniša Šarlija, Marko Kesedžić, Ivan Gambiraža, Mate Dropuljić, Branimir Mijić, Igor Henigsberg, Neven Jovanovic, Tanja |
author_facet | Ćosić, Krešimir Popović, Siniša Šarlija, Marko Kesedžić, Ivan Gambiraža, Mate Dropuljić, Branimir Mijić, Igor Henigsberg, Neven Jovanovic, Tanja |
author_sort | Ćosić, Krešimir |
collection | PubMed |
description | The COVID-19 pandemic has adverse consequences on human psychology and behavior long after initial recovery from the virus. These COVID-19 health sequelae, if undetected and left untreated, may lead to more enduring mental health problems, and put vulnerable individuals at risk of developing more serious psychopathologies. Therefore, an early distinction of such vulnerable individuals from those who are more resilient is important to undertake timely preventive interventions. The main aim of this article is to present a comprehensive multimodal conceptual approach for addressing these potential psychological and behavioral mental health changes using state-of-the-art tools and means of artificial intelligence (AI). Mental health COVID-19 recovery programs at post-COVID clinics based on AI prediction and prevention strategies may significantly improve the global mental health of ex-COVID-19 patients. Most COVID-19 recovery programs currently involve specialists such as pulmonologists, cardiologists, and neurologists, but there is a lack of psychiatrist care. The focus of this article is on new tools which can enhance the current limited psychiatrist resources and capabilities in coping with the upcoming challenges related to widespread mental health disorders. Patients affected by COVID-19 are more vulnerable to psychological and behavioral changes than non-COVID populations and therefore they deserve careful clinical psychological screening in post-COVID clinics. However, despite significant advances in research, the pace of progress in prevention of psychiatric disorders in these patients is still insufficient. Current approaches for the diagnosis of psychiatric disorders largely rely on clinical rating scales, as well as self-rating questionnaires that are inadequate for comprehensive assessment of ex-COVID-19 patients’ susceptibility to mental health deterioration. These limitations can presumably be overcome by applying state-of-the-art AI-based tools in diagnosis, prevention, and treatment of psychiatric disorders in acute phase of disease to prevent more chronic psychiatric consequences. |
format | Online Article Text |
id | pubmed-8751545 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87515452022-01-12 AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients Ćosić, Krešimir Popović, Siniša Šarlija, Marko Kesedžić, Ivan Gambiraža, Mate Dropuljić, Branimir Mijić, Igor Henigsberg, Neven Jovanovic, Tanja Front Psychol Psychology The COVID-19 pandemic has adverse consequences on human psychology and behavior long after initial recovery from the virus. These COVID-19 health sequelae, if undetected and left untreated, may lead to more enduring mental health problems, and put vulnerable individuals at risk of developing more serious psychopathologies. Therefore, an early distinction of such vulnerable individuals from those who are more resilient is important to undertake timely preventive interventions. The main aim of this article is to present a comprehensive multimodal conceptual approach for addressing these potential psychological and behavioral mental health changes using state-of-the-art tools and means of artificial intelligence (AI). Mental health COVID-19 recovery programs at post-COVID clinics based on AI prediction and prevention strategies may significantly improve the global mental health of ex-COVID-19 patients. Most COVID-19 recovery programs currently involve specialists such as pulmonologists, cardiologists, and neurologists, but there is a lack of psychiatrist care. The focus of this article is on new tools which can enhance the current limited psychiatrist resources and capabilities in coping with the upcoming challenges related to widespread mental health disorders. Patients affected by COVID-19 are more vulnerable to psychological and behavioral changes than non-COVID populations and therefore they deserve careful clinical psychological screening in post-COVID clinics. However, despite significant advances in research, the pace of progress in prevention of psychiatric disorders in these patients is still insufficient. Current approaches for the diagnosis of psychiatric disorders largely rely on clinical rating scales, as well as self-rating questionnaires that are inadequate for comprehensive assessment of ex-COVID-19 patients’ susceptibility to mental health deterioration. These limitations can presumably be overcome by applying state-of-the-art AI-based tools in diagnosis, prevention, and treatment of psychiatric disorders in acute phase of disease to prevent more chronic psychiatric consequences. Frontiers Media S.A. 2021-12-28 /pmc/articles/PMC8751545/ /pubmed/35027902 http://dx.doi.org/10.3389/fpsyg.2021.782866 Text en Copyright © 2021 Ćosić, Popović, Šarlija, Kesedžić, Gambiraža, Dropuljić, Mijić, Henigsberg and Jovanovic. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychology Ćosić, Krešimir Popović, Siniša Šarlija, Marko Kesedžić, Ivan Gambiraža, Mate Dropuljić, Branimir Mijić, Igor Henigsberg, Neven Jovanovic, Tanja AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients |
title | AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients |
title_full | AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients |
title_fullStr | AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients |
title_full_unstemmed | AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients |
title_short | AI-Based Prediction and Prevention of Psychological and Behavioral Changes in Ex-COVID-19 Patients |
title_sort | ai-based prediction and prevention of psychological and behavioral changes in ex-covid-19 patients |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8751545/ https://www.ncbi.nlm.nih.gov/pubmed/35027902 http://dx.doi.org/10.3389/fpsyg.2021.782866 |
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