4.6 Article

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

期刊

SENSORS
卷 23, 期 2, 页码 -

出版社

MDPI
DOI: 10.3390/s23020565

关键词

metaverse; healthcare; explainable AI; blockchain; healthcare metaverse; immersive technologies; mixed reality; digital twins; immersive technologies in healthcare; NLP

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This paper proposes the integration of artificial intelligence and blockchain in the metaverse to provide better, faster, and more secure healthcare services. The proposed architecture includes three environments: the doctor's environment, the patient's environment, and the metaverse environment. Doctors and patients interact in the metaverse environment using blockchain technology, and AI models are used for disease prediction and diagnosis. Blockchain ensures data security and transparency.
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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