Effect Analysis of Nursing Intervention on Lower Extremity Deep Venous Thrombosis in Patients

Abstract

In the modern era, nursing intervention is an increased commitment to patient quality and protection that allows nurses to make evidence-based healthcare decisions. The challenging characteristic of patients such as high deep venous thrombosis (DVT) and respiratory embolisms (RE) are significant health conditions that lead to post-operative severe injury and death. In this article, hybrid machine learning (HML) is used for senile patients with lower extremity fractures during the perioperative time and the clinical effectiveness of early stages nursing protocol for deep venous thrombosis of patients and nurses. A three-dimensional shape model of the user interface is shown the examined vessels, which have compression measurements mapped to the surface as colors and virtual image plane representation of DVT. The measures of comprehension have been validated using HML model segmentation experts and contrasted with paired f-tests to reduce the incidence of lower extremity deep venous thrombosis in patients and nurses.