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Analysis of Nursing Safety Incident Characteristics in ENT Surgery Using Deep Learning-Based Medical Knowledge Association Rules | OMICS International| Abstract
ISSN: 2161-119X

Otolaryngology: Open Access
Open Access

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  • Otolaryngol (Sunnyvale,

Analysis of Nursing Safety Incident Characteristics in ENT Surgery Using Deep Learning-Based Medical Knowledge Association Rules

Lin Wei*
Clinical College of Hebei Medical University, Shijiazhuang, 050031, Hebei, China
*Corresponding Author : Lin Wei, Clinical College of Hebei Medical University, Shijiazhuang, 050031, Hebei, China, Email: lin@wei4872.com

Received Date: Nov 02, 2022 / Published Date: Nov 29, 2022

Abstract

It is of nice significance to explore the characteristic factors of surgical nursing safety events in patients with medical specialty surgery and to grasp the characteristics of surgical nursing safety events in medical specialty surgery patients. This paper distributed surgical safety protection for 385 inpatients, and therefore the results showed that there have been fifty two cases of surgical safety nursing events. This experiment found that the confected lesions (95.0% C1: 9.365~21.038), the treatment amount (95.0% CI: 7.147~20.275), throughout hospital treatment (95.0% CI: 8.918-24.237), antibiotic use (95.0% CI: 8.163-21.739), and cardiovascular disease (95.0% CI: 7.926-22.385) square measure the necessary factors moving surgical care; mistreatment the association rule methodology to manage and analyse the most risk factors of surgical infection and haemorrhage in ENT patients will considerably improve the prognosis.

Citation: Wei L (2022) Analysis of Nursing Safety Incident Characteristics in ENT Surgery Using Deep Learning-Based Medical Knowledge Association Rules. Otolaryngol (Sunnyvale) 12: 494.

Copyright: © 2022 Wei L. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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