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Construction of smart medical assurance system based on virtual reality and GANs image recognition

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Abstract

With the rapid and recent development of computer technology and Internet technology, virtual reality technology gradually tends to be mature and perfect, and widely used in various fields of life. At present, virtual reality technology has touched telemedicine activities, and become another intuitive and effective form of service in telemedicine activities. Practitioners in the medical industry pay so much attention to the safety of medical services, which also shows that medical safety has been a major challenge for medical staff since ancient times. Due to the limitations of medical research and the complexity of medical work, it is very difficult to avoid medical errors and improve the safety level of patients. In this paper, virtual reality technology and GAN based image recognition technology are applied in the intelligent medical system. Combining medical image recognition with virtual reality system, an intelligent medical system is designed and implemented. Different from the traditional telemedicine system, the application of the system can achieve remote sharing of three-dimensional surgical images. The medical staff in different areas only need to operate through the network to realize the virtual operation environment, which can not only fully display the operation scene, but also observe from any direction and angle, so as to reduce medical costs and save time. The proposed model is implemented under different scenarios, and the comparison experimental analysis is conducted to validate the performance of the model. Through the simulation, it can be proven that the propose model is efficient, the accuracy is improved to more than 95%, as the system is improved from the perspectives of robustness and accuracy.

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Correspondence to Yunfeng Zhang.

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Li, J., Zhang, Y. Construction of smart medical assurance system based on virtual reality and GANs image recognition. Int J Syst Assur Eng Manag 13, 2517–2530 (2022). https://doi.org/10.1007/s13198-022-01661-x

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  • DOI: https://doi.org/10.1007/s13198-022-01661-x

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