Integrating Technologies in the Metaverse for Enhanced Healthcare and Medical Education

IF 2.9 3区教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

IEEE Transactions on Learning Technologies Pub Date : 2025-02-03 DOI:10.1109/TLT.2025.3537802

Ahmad Chaddad;Yuchen Jiang

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引用次数: 0

Abstract

The concept of the Metaverse, viewed as the ultimate manifestation of the Internet, has gained significant attention due to rapid advances in technologies such as the Internet of Things (IoT) and blockchain. Acting as a bridge between the physical and virtual worlds, the Metaverse has the potential to offer remarkable experiences to its users. This study presents a comprehensive survey of Metaverse techniques, including artificial intelligence, blockchain, IoT, augmented reality, virtual reality, 5G, natural language processing, and digital twins. These Metaverse techniques lead to improved health outcomes and patient care, offering innovative treatments for complex conditions, and advancing medical education. We explore the benefits of the Metaverse by examining its effectiveness in supporting various medical applications and highlight potential research challenges and future trends for the medical Metaverse and education. Although the Metaverse is currently in its early stages, more efforts are required to enable its widespread adoption in the future.

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来源期刊

IEEE Transactions on Learning Technologies COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-

CiteScore

7.50

自引率

5.40%

发文量

审稿时长

>12 weeks

期刊介绍： The IEEE Transactions on Learning Technologies covers all advances in learning technologies and their applications, including but not limited to the following topics: innovative online learning systems; intelligent tutors; educational games; simulation systems for education and training; collaborative learning tools; learning with mobile devices; wearable devices and interfaces for learning; personalized and adaptive learning systems; tools for formative and summative assessment; tools for learning analytics and educational data mining; ontologies for learning systems; standards and web services that support learning; authoring tools for learning materials; computer support for peer tutoring; learning via computer-mediated inquiry, field, and lab work; social learning techniques; social networks and infrastructures for learning and knowledge sharing; and creation and management of learning objects.