ABSTRACT. This paper draws on a substantial body of theoretical and empirical research on multi-modal medical data processing, automated healthcare service delivery, and metaverse- and extended reality-based medical interventions. A quantitative literature review of ProQuest, Scopus, and the Web of Science was carried out throughout June 2024, with search terms including “metaverse- and extended reality-based medical interventions across virtual diagnostic environments” + “artificial intelligence-driven clinical data and health monitoring systems,” “virtual patient simulation and medical sensor data analysis,” and “digital twin healthcare networks.” As research published between 2022 and 2024 was inspected, only 162 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: AMSTAR, Catchii, JBI SUMARI, Litstream, PICO Portal, and SRDR+.

Keywords: artificial intelligence-driven clinical data and health monitoring system; virtual patient simulation; medical sensor data; digital twin healthcare; metaverse- and extended reality-based medical intervention; virtual diagnostic environment

How to cite: Preda, A., Hurjui, M. C., Dumitrescu, C.-O., and Samoilă, A. (2024). “Artificial Intelligence-driven Clinical Data and Health Monitoring Systems, Virtual Patient Simulation and Medical Sensor Data Analysis, and Digital Twin Healthcare Networks for Metaverse- and Extended Reality-based Medical Interventions across Virtual Diagnostic Environments,” American Journal of Medical Research 11(2): 87–102. doi: 10.22381/ajmr11220246.

Received 12 July 2024 • Received in revised form 23 October 2024
Accepted 26 October 2024 • Available online 30 October 2024