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. 2012 Sep;30(7):1245-7.
doi: 10.1016/j.ajem.2011.06.019. Epub 2011 Sep 9.

Artificial neural networks in the diagnosis of acute appendicitis

Ömer Yoldaş  1 , Mesut Tez, Turgut Karaca
Affiliations

Artificial neural networks in the diagnosis of acute appendicitis

Ömer Yoldaş et al. Am J Emerg Med. 2012 Sep.

Abstract

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.

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