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Acute appendicitis diagnosis using artificial neural networks

Issue title: Papers from the 3rd International Conference on Biomedical Engineering and Technology (iCBEB 2014), 25–28 September 2014, Beijing, China

Subtitle:

Guest editors: Edward J. Ciaccio

Article type: Research Article

Authors: Park, Sung Yun | Kim, Sung Min*

Affiliations: Department of Medical Biotechnology, Dongguk University-Seoul, Seoul, Korea

Correspondence: [*] Corresponding author: Sung Min Kim, Department of Medical Biotechnology, Dongguk University-Seoul, 26, Pil-dong 3-ga, Jung-gu, Seoul, Korea. E-mail:[email protected]

Keywords: Alvarado clinical scoring system, acute appendicitis, clinical scoring system, artificial neural network

DOI: 10.3233/THC-150994

Journal: Technology and Health Care, vol. 23, no. s2, pp. S559-S565, 2015

Published: 2015
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Abstract

BACKGROUND: Artificial neural networks is one of pattern analyzer method which are rapidly applied on a bio-medical field.

OBJECTIVE: The aim of this research was to propose an appendicitis diagnosis system using artificial neural networks (ANNs).

METHODS: Data from 801 patients of the university hospital in Dongguk were used to construct artificial neural networks for diagnosing appendicitis and acute appendicitis. A radial basis function neural network structure (RBF), a multilayer neural network structure (MLNN), and a probabilistic neural network structure (PNN) were used for artificial neural network models. The Alvarado clinical scoring system was used for comparison with the ANNs.

RESULTS: The accuracy of the RBF, PNN, MLNN, and Alvarado was 99.80%, 99.41%, 97.84%, and 72.19%, respectively. The area under ROC (receiver operating characteristic) curve of RBF, PNN, MLNN, and Alvarado was 0.998, 0.993, 0.985, and 0.633, respectively.

CONCLUSIONS: The proposed models using ANNs for diagnosing appendicitis showed good performances, and were significantly better than the Alvarado clinical scoring system (p < 0.001). With cooperation among facilities, the accuracy for diagnosing this serious health condition can be improved.

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