title: Use of artificial neural network to predict esophageal varices in patients with HBV related cirrhosis.
abstract: BACKGROUND
  Prediction of esophageal varices in cirrhotic patients by noninvasive methods is still unsatisfactory.
  
  
  OBJECTIVE
  To evaluate the accuracy of an artificial neural network (ANN) in predicting varices in patients with HBV related cirrhosis.
  
  
  METHODS
  An ANN was constructed with data taken from 197 patients with HBV related cirrhosis. The candidates for input nodes of the ANN were assessed by univariate analysis and sensitivity analysis. Five-fold cross validation was performed to avoid over-fitting.
  
  
  RESULTS
  14 variables were reduced by univariate and sensitivity analysis, and an ANN was developed with three variables (platelet count, spleen width and portal vein diameter). With a cutoff value of 0.5. The ANN model has a sensitivity of 96.5%, specificity of 60.4%, positive predictive value of 86.9%, negative predictive value of 86.5% and a diagnostic accuracy of 86.8% for the prediction of varices.
  
  
  CONCLUSIONS
  An ANN may be useful for predicting presence of esophageal varices in patients with HBV related cirrhosis.
authors.affiliation: Department of Gastroenterology and Hepatology, the First Affiliated Hospital of Wenzhou Medical College, Wenzhou, China.
authors.forename: Wan-Dong
authors.initials: WD
authors.lastname: Hong
authors.forename: Yi-Feng
authors.initials: YF
authors.lastname: Ji
authors.forename: Dang
authors.initials: D
authors.lastname: Wang
authors.forename: Tan-Zhou
authors.initials: TZ
authors.lastname: Chen
authors.forename: Qi-Huai
authors.initials: QH
authors.lastname: Zhu
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