Orthopedic surgery and care during the perioperative period are the key to the treatment of orthopedic diseases, which can quickly and effectively treat orthopedic diseases and can quickly recover during the perioperative period. Therefore, this paper focuses on the observation of the effect of intelligent machine-assisted surgery and perioperative care, combined with smart wearable devices and C-arm camera calibration; the details of the bone surgery are assisted by the machine, and then the recognition ability is accelerated by writing into the digital bone bank. Based on machine vision, CNN training and learning are designed to design a machine-assisted perioperative nursing method. This paper also designed a bone surgery test experiment and perioperative adverse event data analysis, combined with the data obtained from the experiment, designed a comparison experiment with traditional surgery and perioperative nursing. The experimental results show that the success rate of machine-assisted surgery is increased by nearly 2%-15% compared with traditional surgery; and the rehabilitation degree of machine-assisted perioperative nursing is 15.83% higher than that of traditional perioperative nursing.
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