ABSTRACT. This paper provides a systematic literature review of studies investigating digital twin smart healthcare systems pivotal in remote patient monitoring by health issue and medical data sharing, consultation and diagnostic accuracy, and operating room availability detection. The analysis highlights that clinical decision support and metaverse-based healthcare systems can improve patient care and experience by medical record tracking and sharing in computer-based virtual patient environments. Throughout January 2023, a quantitative literature review of the Web of Science, Scopus, and ProQuest databases was performed, with search terms including “the healthcare metaverse” + “virtual medical and human‒computer interaction technologies,” “multidimensional big clinical and biological data,” and “extended digital twin-based medical condition diagnosis.” As research published between 2022 and 2023 was inspected, only 166 articles satisfied the eligibility criteria, and 19 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, Distiller SR, MMAT, and ROBIS.

Keywords: human‒computer interaction; multidimensional big clinical and biological data; digital twin; medical condition diagnosis; healthcare metaverse

How to cite: Popescu, G.-C., and Cug, J. (2023). “Virtual Medical and Human‒Computer Interaction Technologies, Multidimensional Big Clinical and Biological Data, and Extended Digital Twin-based Medical Condition Diagnosis in the Healthcare Metaverse,” American Journal of Medical Research 10(1): 7–21. doi: 10.22381/ajmr10120231.

Received 26 February 2023 • Received in revised form 20 April 2023
Accepted 24 April 2023 • Available online 30 April 2023