Digitization and automation have always had an immense impact on healthcare. It embraces every new and advanced technology. Recently the world has witnessed the prominence of the metaverse which is an emerging technology in digital space. The metaverse has huge potential to provide a plethora of health services seamlessly to patients and medical professionals with an immersive experience. This paper proposes the amalgamation of artificial intelligence and blockchain in the metaverse to provide better, faster, and more secure healthcare facilities in digital space with a realistic experience. Our proposed architecture can be summarized as follows. It consists of three environments, namely the doctor’s environment, the patient’s environment, and the metaverse environment. The doctors and patients interact in a metaverse environment assisted by blockchain technology which ensures the safety, security, and privacy of data. The metaverse environment is the main part of our proposed architecture. The doctors, patients, and nurses enter this environment by registering on the blockchain and they are represented by avatars in the metaverse environment. All the consultation activities between the doctor and the patient will be recorded and the data, i.e., images, speech, text, videos, clinical data, etc., will be gathered, transferred, and stored on the blockchain. These data are used for disease prediction and diagnosis by explainable artificial intelligence (XAI) models. The GradCAM and LIME approaches of XAI provide logical reasoning for the prediction of diseases and ensure trust, explainability, interpretability, and transparency regarding the diagnosis and prediction of diseases. Blockchain technology provides data security for patients while enabling transparency, traceability, and immutability regarding their data. These features of blockchain ensure trust among the patients regarding their data. Consequently, this proposed architecture ensures transparency and trust regarding both the diagnosis of diseases and the data security of the patient. We also explored the building block technologies of the metaverse. Furthermore, we also investigated the advantages and challenges of a metaverse in healthcare.

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Metaverse in Healthcare Integrated with Explainable AI and Blockchain: Enabling Immersiveness, Ensuring Trust, and Providing Patient Data Security

The paper focuses on analysing the potential benefits and challenges of the Metaverse, particularly in the field of research in the tourism and food and wine sectors. The Metaverse is part of the new generation of the internet known as web 3.0, which also includes AI, blockchain and other digital innovations. The food marketing and tourism sectors are the main fields where companies are experimenting with solutions to offer people a fully functioning immersive Metaverse experience. This paper aims to highlight the potential impact of the Metaverse on tourism sectors as well as on research activities. Open challenges concern the social acceptance, affordability, and environmental sustainability of these technologies. Research is needed on the Metaverse’s ability to reduce bias and accurately simulate real experiences, as well as on tourists’ perceptions, attitudes, and willingness to pay for mediated experiences. Another important issue is the management of sensitive data that will travel through the Metaverse. Looking forward, the Metaverse has the potential to become a valuable tool for advancing tourism research through virtual collaboration and interdisciplinary research projects.

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Travelling the Metaverse: Potential Benefits and Main Challenges for Tourism Sectors and Research Applications

Medical digital twins, which represent medical assets, play a crucial role in connecting the physical world to the metaverse, enabling patients to access virtual medical services and experience immersive interactions with the real world. One serious disease that can be diagnosed and treated using this technology is cancer. However, the digitalization of such diseases for use in the metaverse is a highly complex process. To address this, this study aims to use machine learning (ML) techniques to create real-time and reliable digital twins of cancer for diagnostic and therapeutic purposes. The study focuses on four classical ML techniques that are simple and fast for medical specialists without extensive Artificial Intelligence (AI) knowledge, and meet the requirements of the Internet of Medical Things (IoMT) in terms of latency and cost. The case study focuses on breast cancer (BC), the second most prevalent form of cancer worldwide. The study also presents a comprehensive conceptual framework to illustrate the process of creating digital twins of cancer, and demonstrates the feasibility and reliability of these digital twins in monitoring, diagnosing, and predicting medical parameters.

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Metaverse and Healthcare: Machine Learning-Enabled Digital Twins of Cancer

The Metaverse is an emerging technology to make virtual environments for users to benefit from a huge number of virtual services, while users experience immersive interactions with the real world. Digital twins, which are representatives of assets in this virtual world, play an important role to connect this environment to the actual world. Therefore, translating problematic assets, objects, and disease like cancers to this cyber world provide patients with this opportunity to benefit from its advantages. This study aims to conceptualize an approach to how machine learning (ML) can realize real-time and robust digital twins of cancers to be used in the Metaverse for diagnosis and treatment. While there are a large number of ML methods, which have advantages based on the various types of healthcare data, four classic ML techniques, including ML linear regression (ML LR), decision tree regression (DTR), Random Forest Regression (RFR), and Gradient Boosting Algorithm (GBA), have been employed to implement the main part of this approach in this research. Moreover, a comprehensive conceptual framework of the ML digital twinning method has been presented to illustrate the process of digital twining cancers with different medical data. 

Cancer Digital Twins in Metaverse

There has been a growing interest in the “metaverse,” and discourse about how this platform may contribute to different fields of science is already beginning to emerge. In this paper, we discuss key opportunities and uncertainties about how a metaverse might contribute to advancing knowledge in the interdisciplinary field of the built environment and public health aimed at reducing noncommunicable diseases.

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The Metaverse, the Built Environment, and Public Health: Opportunities and Uncertainties

The metaverse integrates physical and virtual realities, enabling humans and their avatars to interact in an environment supported by technologies such as high-speed internet, virtual reality, augmented reality, mixed and extended reality, blockchain, digital twins and artificial intelligence (AI), all enriched by effectively unlimited data. The metaverse recently emerged as social media and entertainment platforms, but extension to healthcare could have a profound impact on clinical practice and human health. As a group of academic, industrial, clinical and regulatory researchers, we identify unique opportunities for metaverse approaches in the healthcare domain. A metaverse of ‘medical technology and AI’ (MeTAI) can facilitate the development, prototyping, evaluation, regulation, translation and refinement of AI-based medical practice, especially medical imaging-guided diagnosis and therapy. Here, we present metaverse use cases, including virtual comparative scanning, raw data sharing, augmented regulatory science and metaversed medical intervention. We discuss relevant issues on the ecosystem of the MeTAI metaverse including privacy, security and disparity. We also identify specific action items for coordinated efforts to build the MeTAI metaverse for improved healthcare quality, accessibility, cost-effectiveness and patient satisfaction. The metaverse is gaining prominence in industry, academia and social media. Wang and colleagues envision a medical technology and AI ecosystem, and present this perspective on the future of healthcare in the metaverse. 

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Xuan Tang

Papers

Development of metaverse for intelligent healthcare

A Shared Passion for Optics Education: John Greivenkamp and Harrison Barrett