Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Comparative Study
. 1996 Jan;40(3):227-33.
doi: 10.1016/0020-7101(95)01147-1.

Comparison of different neural network algorithms in the diagnosis of acute appendicitis

Affiliations
Comparative Study

Comparison of different neural network algorithms in the diagnosis of acute appendicitis

E Pesonen et al. Int J Biomed Comput. 1996 Jan.

Abstract

Four different neural network algorithms, binary adaptive resonance theory (ART1), self-organizing map, learning vector quantization and back-propagation, were compared in the diagnosis of acute appendicitis with different parameter groups. The results show that supervised learning algorithms learning vector quantization and back-propagation were better than unsupervised algorithms in this medical decision making problem. The best results were obtained with the learning vector quantization. The self-organizing map algorithm showed good specificity, but this was in conjunction with lower sensitivity. The best parameter group was found to be the clinical signs. It seems beneficial to design a decision support system which uses these methods in the decision making process.

PubMed Disclaimer

Similar articles

Cited by

Publication types

LinkOut - more resources