Wearable Patient Monitoring and Metaverse-enabled Healthcare Systems, Immersive Medical Simulation and Remote Care Technologies, and Deep Learning Disease Prediction and Diagnosis Algorithms for Artificial Intelligence-powered Individualized Treatments in Virtual Clinical Settings
Ileana-Diana Diaconu*ABSTRACT. With increasing evidence of wearable haptic devices, real-time patient data monitoring, virtual reality surgery simulation, and healthcare metaverse systems, there is an essential demand for comprehending whether metaverse-enabled healthcare systems enhance patient satisfaction and medical interventions, biological parameter assessment, suspected case screening and management, virtual care and digital diagnostics, and surgical intervention delivery monitoring. A quantitative literature review of ProQuest, Scopus, and the Web of Science was carried out throughout January 2024, with search terms including “artificial intelligence-powered individualized treatments in virtual clinical settings” + “wearable patient monitoring and metaverse-enabled healthcare systems,” “immersive medical simulation and remote care technologies,” and “deep learning disease prediction and diagnosis algorithms.” As research published between 2022 and 2024 was inspected, only 174 articles satisfied the eligibility criteria, and 31 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, CADIMA, Eppi-Reviewer, JBI SUMARI, Litstream, and SWIFT-Active Screener.
Keywords: wearable patient monitoring; metaverse-enabled healthcare system; immersive medical simulation; remote care; deep learning disease prediction and diagnosis algorithm; artificial intelligence-powered individualized treatment
How to cite: Diaconu, I.-D. (2024). “Wearable Patient Monitoring and Metaverse-enabled Healthcare Systems, Immersive Medical Simulation and Remote Care Technologies, and Deep Learning Disease Prediction and Diagnosis Algorithms for Artificial Intelligence-powered Individualized Treatments in Virtual Clinical Settings,” American Journal of Medical Research 11(1): 39–54. doi: 10.22381/ajmr11120243.
Received 8 February 2024 • Received in revised form 21 April 2024
Accepted 26 April 2024 • Available online 30 April 2024