• Am J Emerg Med · Sep 2012

    Artificial neural networks in the diagnosis of acute appendicitis.

    • Ömer Yoldaş, Mesut Tez, and Turgut Karaca.
    • Ordu State Hospital, 52000, Ordu, Turkey.
    • Am J Emerg Med. 2012 Sep 1;30(7):1245-7.

    AbstractThe 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.Copyright © 2012 Elsevier Inc. All rights reserved.

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

What will the 'Medical Journal of You' look like?

Start your free 21 day trial now.

We guarantee your privacy. Your email address will not be shared.