ABSTRACT. In this article, previous research findings were cumulated indicating that digital twin smart healthcare systems, artificial intelligence-based medical imaging data, Internet of Medical Things devices, and sensor-based physiological parameter measurement can be leveraged in disease diagnosis and treatment accuracy for immersive medical experiences. Throughout February 2024, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “computer-based virtual patient environments” + “metaverse-based medical simulations,” “3D holographic and clinical decision support systems,” and “wearable medical technologies.” As research published between 2022 and 2024 was inspected, only 171 articles satisfied the eligibility criteria, and 29 mainly empirical sources were selected. Data visualization tools: Dimensions (bibliometric mapping) and VOSviewer (layout algorithms). Reporting quality assessment tool: PRISMA. Methodological quality assessment tools include: AMSTAR, Colandr, Eppi-Reviewer, JBI SUMARI, Litstream, and MMAT.

Keywords: metaverse; clinical decision support system; wearable medical technology; Internet of Things; digital health service; computer-based virtual patient environment

How to cite: Jandacka, J., Bonciu, C. I., Dragomir, M., and Curteanu, A.-B. (2024). “Metaverse-based Medical Simulations, 3D Holographic and Clinical Decision Support Systems, and Wearable Medical Technologies for Internet of Things-based Digital Health Services in Computer-based Virtual Patient Environments,” American Journal of Medical Research 11(1): 23–38. doi: 10.22381/ajmr11120242.

Received 7 March 2024 • Received in revised form 22 April 2024
Accepted 24 April 2024 • Available online 30 April 2024