An efficient and robust multi-scenario artificial intelligent medical model based on metaverse

Autor: Jiuwen ZHU, Yubing ZHOU, Hongbiao SI, Liang XU
Jazyk: čínština
Rok vydání: 2024
Předmět:
Zdroj: 大数据, Vol 10, Pp 122-139 (2024)
Druh dokumentu: article
ISSN: 2096-0271
DOI: 10.11959/j.issn.2096-0271.2023006
Popis: Unbalanced medical and educational resources, low intelligence of the medical system, and reliance on individual experience in surgical operations are common in medical trade.The metaverse with immersive and interactive features is an effective tool to solve the problem.However, most of the existing solutions are based on a specific technology of virtual reality or artificial intelligence or a specific operation, and there is little systematic research on the multifunctional and multi-scenario medical metaverse.Therefore, a multi-scenario artificial intelligent medical model based on metaverse (MetaMed) was proposed, which elaborated the bottom-up implementations from four layers, including the access layer, data layer, technology layer and application layer.MetaMed was mathematically applied in five medical scenarios, i.e., intelligent surgery, online consultation, medical education, robotic surgery and outpatient registration scenarios, which provides references for the construction of medical metaverse in the future.
Databáze: Directory of Open Access Journals