Department of Nursing Department, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China.
Chinese Academy of Sciences, Sichuan Translational Medicine Research Hospital, Chengdu 610072, Sichuan, China.
J Healthc Eng. 2022 Apr 18;2022:5719897. doi: 10.1155/2022/5719897. eCollection 2022.
Neurosurgery is mainly for the treatment of head trauma, cerebrovascular disease, brain tumors, and spinal cord disorders. These operations are difficult and risky, so disability and mortality are high. To reduce the risk of surgery, reduce postoperative complications, and improve the treatment effect of patients, this article applies deep learning and microscopic imaging to the nursing process of neurosurgery. Through deep learning and microscopic imaging, doctors can learn about patients during surgery. The specific situation of the trauma site, after which surgery is performed according to the situation, effectively reduces the casualties, reduces the loss of patients, and provides a reference for the research of neurosurgery nursing. Research results prove that deep learning and microscopic imaging can play an important role in the nursing process of neurosurgery. Compared with conventional treatment methods, microscopic imaging treatment can effectively improve the treatment effect, and the operation time for patients is less than that of conventional treatment. About 20% and the incidence of postoperative complications is lower than 30%, which can effectively reduce the cost to patients and improve the quality of treatment.
神经外科主要治疗头部创伤、脑血管病、脑肿瘤和脊髓疾病。这些手术难度大、风险高，因此致残率和死亡率较高。为降低手术风险、减少术后并发症、提高患者治疗效果，本文将深度学习和显微镜成像应用于神经外科护理过程中。通过深度学习和显微镜成像，医生可以在手术中了解患者创伤部位的具体情况，然后根据情况进行手术，有效降低了伤亡率，减少了患者的损失，为神经外科护理的研究提供了参考。研究结果证明，深度学习和显微镜成像可以在神经外科护理过程中发挥重要作用。与常规治疗方法相比，显微镜成像治疗可以有效提高治疗效果，且患者的手术时间比常规治疗少约 20%，术后并发症发生率低于 30%，可以有效降低患者的治疗成本，提高治疗质量。
