ABSTRACT. This article reviews and advances existing literature concerning personalized medical care and multiple patient attribute analysis and diagnosis. In this research, previous findings were cumulated showing that metaverse and extended reality technologies can be harnessed by use of accurate and personalized digital patient diagnosis based on medical data in 3D medical treatment management, and the contribution to the literature is by indicating that metaverse and blockchain technologies can assist healthcare metaverse services and immersive medical procedures and interventions with regard to multifaceted health conditions in immersive medical simulation environments. Throughout February 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “digital twin-based clinical treatments in decentralized 3D virtual reality environments” + “multimodal deep learning-based medical emergency management,” “wearable device-based physiological data examination,” and “metaverse-based medical imaging and extended reality technologies.” As research published between 2022 and 2023 was inspected, only 162 articles satisfied the eligibility criteria, and 21 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: AXIS, MMAT, ROBIS, and SRDR.

Keywords: deep learning; wearable device; physiological data examination; metaverse-based medical imaging; extended reality; digital twin-based clinical treatment

How to cite: Rowland, M. (2023). “Multimodal Deep Learning-based Medical Emergency Management, Wearable Device-based Physiological Data Examination, and Metaverse-based Medical Imaging and Extended Reality Technologies for Digital Twin-based Clinical Treatments in Decentralized 3D Virtual Reality Environments,” American Journal of Medical Research 10(1): 82–96. doi: 10.22381/ajmr10120236.

Received 8 March 2023 • Received in revised form 25 April 2023
Accepted 27 April 2023 • Available online 30 April 2023