Deep Learning and Microscopic Imaging in the Nursing Process of Neurosurgery Operation

Abstract

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.

An Effective Deep Learning Model to Discriminate Coronavirus Disease From Typical Pneumonia

“…Such developments supply additional proof that optimal performance can be obtained via deep architecture (Deepalakshmi et al, 2021;Waleed et al, 2021). The CNN-based image recognition models have been capable of distinguishing a considerable number of targets, and the obtained recognition accuracies exceed the standard individual's level (Jiang, 2022). Therefore, it can be concluded that, deep CNN can be exploited for realizing such developments also in the COVID-19 discrimination too.…”

Retracted: Deep Learning and Microscopic Imaging in the Nursing Process of Neurosurgery Operation

“…This article has been retracted by Hindawi following an investigation undertaken by the publisher [ 1 ]. This investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process: Discrepancies in scope Discrepancies in the description of the research reported Discrepancies between the availability of data and the research described Inappropriate citations Incoherent, meaningless and/or irrelevant content included in the article Peer-review manipulation …”

“…Tis article has been retracted by Hindawi following an investigation undertaken by the publisher [1]. Tis investigation has uncovered evidence of one or more of the following indicators of systematic manipulation of the publication process:…”