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Deep Learning-Based Medical Data Association Rules Method Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery | OMICS International| Abstract
ISSN: 2161-119X

Otolaryngology: Open Access
Open Access

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  • Research Article   
  • Otolaryngol (Sunnyvale) ,

Deep Learning-Based Medical Data Association Rules Method Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery

Asit Arora*
Departments of ENT, Endocrine and Thyroid Surgery, Imperial College Healthcare NHS Trust, St. Mary's Hospital, Praed St, London W2 1NY, UK
*Corresponding Author : Asit Arora, Departments of ENT, Endocrine and Thyroid Surgery, Imperial College Healthcare NHS Trust, St. Mary's Hospital, Praed St, London W2 1NY, UK, Tel: +447887001142, Email: aroraasit@doctors.org.uk

Received Date: Nov 28, 2022 / Published Date: Dec 29, 2022

Abstract

Otolaryngology is a fairly prevalent condition, and complications including infection and significant bleeding frequently happen during surgery, which pose a serious risk to the patients' mortality. Exploring the distinctive characteristics of postoperative nursing safety events in patients who have undergone otolaryngology surgery and comprehending the distinctive features of postoperative nursing safety events in otolaryngology surgery patients are of utmost importance. 52 incidences of postoperative safety nursing incidents were identified by this study's preoperative safety protection for 385 inpatients. According to this study, the main factors influencing postoperative care are confected lesions (95.0% C1: 9.365–21.038), the treatment period (95.0% CI: 7.147–20.275), during hospitalisation (95.0% CI: 8.918–24.237), antibiotic use (95.0% CI: 8.163-21.739), and hypertension (95.0% CI: 7.926-22.385). Using the association rule method to analyse and control the major risk.

Citation: Arora A (2022) Deep Learning-Based Medical Data Association Rules Method Analysis of Characteristic Factors of Nursing Safety Incidents in ENT Surgery. Otolaryngol (Sunnyvale) 12: 496.

Copyright: © 2022 Arora A. 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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