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Query: UMLS:C0085693 (acute appendicitis)
3,606 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

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.
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PMID:Comparison of different neural network algorithms in the diagnosis of acute appendicitis. 866 75