Application of artificial neural networks for diagnosing acute appendicitis

Sung Yun Park, Sangjoon Lee, Jae Hoon Jeong, Sung Min Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The purpose of this study is to develop an appendicitis diagnosis system, by using artificial neural networks (ANNs). Acute appendicitis is one of the most common surgical emergencies of the abdomen. Various methods have been developed to diagnose appendicitis, but these methods have not shown good performance in the Middle East and Asia, or even in the West. We used the structures of ANNs with 801 patients. These various structures are a multilayer neural network structure (MLNN), a radial basis function neural network structure (RBF), and a probabilistic neural network structure (PNN). The Alvarado clinical scoring system was used for comparison with the ANNs. The accuracy of MLNN, RBF, PNN, and Alvarado was 97.84%, 99.80%, 99.41% and 72.19%, respectively. The AUC of MLNN, RBF, PNN, and Alvarado was 0.985, 0.998, 0.993, and 0.633, respectively. The performance of ANNs was significantly better than the Alvarado clinical scoring system (P<0.001). The models developed to diagnose appendicitis using ANNs showed good performance. We consider that the developed models can help junior clinical surgeons diagnose appendicitis.

Original languageEnglish
Title of host publicationApplied Science and Precision Engineering Innovation
Pages445-450
Number of pages6
DOIs
StatePublished - 2014
EventInternational Applied Science and Precision Engineering Conference 2013, ASPEC 2013 - NanTou, Taiwan, Province of China
Duration: 18 Oct 201322 Oct 2013

Publication series

NameApplied Mechanics and Materials
Volume479-480
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

ConferenceInternational Applied Science and Precision Engineering Conference 2013, ASPEC 2013
Country/TerritoryTaiwan, Province of China
CityNanTou
Period18/10/1322/10/13

Keywords

  • Abdomen
  • Appendicitis
  • Area under the ROC curve
  • Artificial neural network
  • Clinical scoring system

Fingerprint

Dive into the research topics of 'Application of artificial neural networks for diagnosing acute appendicitis'. Together they form a unique fingerprint.

Cite this