ABSTRACT. Based on an in-depth survey of the literature, the purpose of the paper is to explore artificial intelligence analysis tool-based patient feedback, smart clinical diagnosis, medical imaging data acquisition, and deep learning metaverse medical services. Throughout January 2024, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “clinical workflow virtualization and wearable sensor-based healthcare system performance accuracy” + “real-time 3D virtual diagnosis and treatment simulations,” “artificial intelligence-powered medical services and devices,” and “metaverse- and extended reality-based medical interventions.” As research published between 2022 and 2024 was inspected, only 183 articles satisfied the eligibility criteria, and 27 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: Abstrackr, Citationchaser, DistillerSR, Eppi-Reviewer, JBI SUMARI, and METAGEAR package for R.

Keywords: real-time 3D virtual diagnosis and treatment simulation; artificial intelligence; medical services and devices; metaverse; clinical workflow virtualization; wearable sensor-based healthcare system performance

How to cite: Țucmeanu, E. R., and Almășan, A. I. (2024). “Real-Time 3D Virtual Diagnosis and Treatment Simulations, Artificial Intelligence-powered Medical Services and Devices, and Metaverse- and Extended Reality-based Medical Interventions for Clinical Workflow Virtualization and Wearable Sensor-based Healthcare System Performance Accuracy,” American Journal of Medical Research 11(1): 7–22. doi: 10.22381/ajmr11120241.

Received 22 February 2024 • Received in revised form 24 April 2024
Accepted 27 April 2024 • Available online 30 April 2024