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pubmed-article:14691625pubmed:issue12lld:pubmed
pubmed-article:14691625pubmed:dateCreated2003-12-23lld:pubmed
pubmed-article:14691625pubmed:abstractTextPostoperative nausea and vomiting (PONV) are still frequent side-effects after general anaesthesia. These unpleasant symptoms for the patients can be sufficiently reduced using a multimodal antiemetic approach. However, these efforts should be restricted to risk patients for PONV. Thus, predictive models are required to identify these patients before surgery. So far all risk scores to predict PONV are based on results of logistic regression analysis. Artificial neural networks (ANN) can also be used for prediction since they can take into account complex and non-linear relationships between predictive variables and the dependent item. This study presents the development of an ANN to predict PONV and compares its performance with two established simplified risk scores (Apfel's and Koivuranta's scores).lld:pubmed
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pubmed-article:14691625pubmed:authorpubmed-author:MorinA MAMlld:pubmed
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pubmed-article:14691625pubmed:pagination1132-8lld:pubmed
pubmed-article:14691625pubmed:dateRevised2006-11-15lld:pubmed
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pubmed-article:14691625pubmed:year2003lld:pubmed
pubmed-article:14691625pubmed:articleTitle[Prediction of postoperative nausea and vomiting using an artificial neural network].lld:pubmed
pubmed-article:14691625pubmed:affiliationKlinik für Innere Medizin, Kreiskrankenhaus Günzburg.lld:pubmed
pubmed-article:14691625pubmed:publicationTypeJournal Articlelld:pubmed
pubmed-article:14691625pubmed:publicationTypeEnglish Abstractlld:pubmed
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