Artificial neural networks in the diagnosis of acute appendicitis

被引：20

作者：

Yoldas, Omer ^{[2
]}

Tez, Mesut ^{[1
]}

Karaca, Turgut ^{[3
]}

机构：

[1] Ankara Numune Teaching & Res Hosp, Surg Clin 5, TR-06100 Ankara, Turkey

[2] Ordu State Hosp, TR-52000 Ordu, Turkey

[3] Occupat Dis Hosp, TR-06280 Ankara, Turkey

来源：

AMERICAN JOURNAL OF EMERGENCY MEDICINE | 2012年 / 30卷 / 07期

关键词：

SUSPECTED APPENDICITIS; TESTS;

D O I：

10.1016/j.ajem.2011.06.019

中图分类号：

R4 [临床医学];

学科分类号：

1002 ; 100602 ;

摘要：

The aim of the study was to assess the role of artificial neural networks in the diagnosis of acute appendicitis in patients presenting with right lower abdominal pain. Data from 156 patients presenting with suspected appendicitis over a 12-month period to a rural hospital were collected prospectively. The sensitivity, specificity, and positive and negative predictive values of the artificial neural network were 100%, 97.2%, 96.0%, and 100% respectively. Artificial neural networks can be an effective tool for accurately diagnosing acute appendicitis and may reduce unnecessary appendectomies. (C) 2012 Elsevier Inc. All rights reserved.

引用

页码：1245 / 1247

页数：3

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