ABSTRACT. This paper provides a systematic literature review of studies investigating visual medical data and Internet of Things-based smart health monitoring systems. Throughout February 2024, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “blockchain-based healthcare metaverse” + “Internet of Things-based smart health monitoring and virtual patient simulation systems,” “deep learning-based medical imaging and brain–computer interface technologies,” and “digital twin-based clinical and medical care processes.” As research published between 2022 and 2024 was inspected, only 177 articles satisfied the eligibility criteria, and 33 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, CADIMA, DistillerSR, Litstream, Nested Knowledge, and R package and Shiny app citationchaser.

Keywords: Internet of Things-based smart health monitoring; virtual patient simulation; deep learning-based medical imaging; brain–computer interface; digital twin-based clinical and medical care; blockchain-based healthcare metaverse

How to cite: Pera, A. (2024). “Internet of Things-based Smart Health Monitoring and Virtual Patient Simulation Systems, Deep Learning-based Medical Imaging and Brain–Computer Interface Technologies, and Digital Twin-based Clinical and Medical Care Processes in the Blockchain-based Healthcare Metaverse,” American Journal of Medical Research 11(1): 87–102. doi: 10.22381/ajmr11120246.

Received 11 March 2024 • Received in revised form 26 April 2024
Accepted 27 April 2024 • Available online 30 April 2024