title: Electroencephalographic staging of hepatic encephalopathy by an artificial neural network and an expert system.
abstract: OBJECTIVE
  To provide an objective EEG assessment of hepatic encephalopathy (HE), we set up and tested an entirely automatic procedure based on an artificial neural network-expert system software (ANNESS).
  
  
  METHODS
  A training set sample of 50 EEG (group A) and a test sample of 50 EEG (group B) of 100 cirrhotic patients were considered. The EEGs had been visually classified by an expert electroencephalographer, using a modified five-degree Parsons-Simith classification of HE. The efficiency of the ANNESS, trained in group A, was tested in group B.
  
  
  RESULTS
  Both the ANNESS and the visually-based classifications were found to be correlated to liver insufficiency, as assessed by the Child-Pugh score (Spearman's coefficient rho=0.485, P<0.0001; rho=0.489, P<0.0001, respectively) and by the biochemical indexes of hepatic function (bilirubin: rho=0.31 vs. 0.27; albumin: rho=-0.13 vs. -0.18; prothrombin time rho=-0.35 vs. -0.52). The classifications were found to be correlated to each other (rho=0.84 P<0.0001, Cohen's kappa=0.55). However, the ANNESS overestimated grade 2 EEG alterations.
  
  
  CONCLUSIONS
  An ANNESS-based classification of EEG in HE provided data comparable with a visually-based classification, except for mild alterations (class 2) that tended to be overestimated. Further optimization of automatic EEG staging of HE is desirable, as well as a prospective clinical evaluation.
authors.affiliation: Clinica Medica 5, Università di Padova, Viale Giustiniani 2, 35128 Padova, Italy.
authors.forename: A
authors.initials: A
authors.lastname: Pellegrini
authors.forename: E
authors.initials: E
authors.lastname: Ubiali
authors.forename: R
authors.initials: R
authors.lastname: Orsato
authors.forename: S
authors.initials: S
authors.lastname: Schiff
authors.forename: A
authors.initials: A
authors.lastname: Gatta
authors.forename: A
authors.initials: A
authors.lastname: Castellaro
authors.forename: A
authors.initials: A
authors.lastname: Casagrande
authors.forename: P
authors.initials: P
authors.lastname: Amodio
mesh_terms: D000368:Aged; D004502:Education, Medical, Continuing; D004569:Electroencephalography / Q000379:methods; D005260:Female; D006501:Hepatic Encephalopathy / Q000209:etiology / Q000503:physiopathology*; D006801:Humans; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer