A Framework of AI-Based Approaches to Improving eHealth Literacy and Combating Infodemic

Abstract

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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.

Keywords

• AI
• eHealth literacy
• education
• infodemic
• public health