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A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic
The global COVID-19 pandemic has put everyone in an urgent need of accessing and comprehending health information online. Meanwhile, there has been vast amount of information/misinformation/disinformation generated over the Internet, particularly social media platforms, resulting in an infodemic. Th...
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/PMC8669242/ https://www.ncbi.nlm.nih.gov/pubmed/34917575 http://dx.doi.org/10.3389/fpubh.2021.755808 |
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author | Liu, Tianming Xiao, Xiang |
author_facet | Liu, Tianming Xiao, Xiang |
author_sort | Liu, Tianming |
collection | PubMed |
description | The global COVID-19 pandemic has put everyone in an urgent need of accessing and comprehending health information online. Meanwhile, there has been vast amount of information/misinformation/disinformation generated over the Internet, particularly social media platforms, resulting in an infodemic. This public health crisis of COVID-19 pandemic has put each individual and the entire society in a test: what is the level of eHealth literacy is needed to seek accurate health information from online resources and to combat infodemic during a pandemic? This article aims to summarize the significances and challenges of improving eHealth literacy in both communicable (e.g., COVID-19) and non-communicable diseases [e.g., cancer, Alzheimer's disease, and cardiovascular diseases (CVDs)]. Also, this article will make our recommendations of a general framework of AI-based approaches to improving eHealth literacy and combating infodemic, including AI-augmented lifelong learning, AI-assisted translation, simplification, and summarization, and AI-based content filtering. This general framework of AI-based approaches to improving eHealth literacy and combating infodemic has the general advantage of matching the right online health information to the right people. |
format | Online Article Text |
id | pubmed-8669242 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86692422021-12-15 A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic Liu, Tianming Xiao, Xiang Front Public Health Public Health The global COVID-19 pandemic has put everyone in an urgent need of accessing and comprehending health information online. Meanwhile, there has been vast amount of information/misinformation/disinformation generated over the Internet, particularly social media platforms, resulting in an infodemic. This public health crisis of COVID-19 pandemic has put each individual and the entire society in a test: what is the level of eHealth literacy is needed to seek accurate health information from online resources and to combat infodemic during a pandemic? This article aims to summarize the significances and challenges of improving eHealth literacy in both communicable (e.g., COVID-19) and non-communicable diseases [e.g., cancer, Alzheimer's disease, and cardiovascular diseases (CVDs)]. Also, this article will make our recommendations of a general framework of AI-based approaches to improving eHealth literacy and combating infodemic, including AI-augmented lifelong learning, AI-assisted translation, simplification, and summarization, and AI-based content filtering. This general framework of AI-based approaches to improving eHealth literacy and combating infodemic has the general advantage of matching the right online health information to the right people. Frontiers Media S.A. 2021-11-30 /pmc/articles/PMC8669242/ /pubmed/34917575 http://dx.doi.org/10.3389/fpubh.2021.755808 Text en Copyright © 2021 Liu and Xiao. 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 | Public Health Liu, Tianming Xiao, Xiang A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic |
title | A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic |
title_full | A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic |
title_fullStr | A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic |
title_full_unstemmed | A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic |
title_short | A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic |
title_sort | framework of ai-based approaches to improving ehealth literacy and combating infodemic |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8669242/ https://www.ncbi.nlm.nih.gov/pubmed/34917575 http://dx.doi.org/10.3389/fpubh.2021.755808 |
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