title: The accuracy of artificial neural networks in predicting long-term outcome after traumatic brain injury.
abstract: OBJECTIVE
  This study compared the accuracy of artificial neural networks to multiple regression and classification and regression trees in predicting outcomes of 1,644 patients in the Traumatic Brain Injury Model Systems database 1 year after injury.
  
  
  METHODS
  Data from rehabilitation admission were used to predict discharge scores on the Functional Independence Measure, the Disability Rating Scale, and the Community Integration Questionnaire.
  
  
  RESULTS
  Artificial neural networks did not demonstrate greater accuracy in predicting outcomes than did the more widely used method of multiple regression. Both of these methods outperformed classification and regression trees.
  
  
  CONCLUSIONS
  Because of the sophisticated form of multiple regression with splines that was used, firm conclusions are limited about the relative accuracy of artificial neural networks compared to more widely used forms of multiple regression.
authors.affiliation: Research Center for Health Care Decision-making, Inc, Wyndmoor, PA 19038, USA. msegal@healthcaredecisions.org
authors.forename: Mary E
authors.initials: ME
authors.lastname: Segal
authors.forename: Philip H
authors.initials: PH
authors.lastname: Goodman
authors.forename: Richard
authors.initials: R
authors.lastname: Goldstein
authors.forename: Walter
authors.initials: W
authors.lastname: Hauck
authors.forename: John
authors.initials: J
authors.lastname: Whyte
authors.forename: John W
authors.initials: JW
authors.lastname: Graham
authors.forename: Marcia
authors.initials: M
authors.lastname: Polansky
authors.forename: Flora M
authors.initials: FM
authors.lastname: Hammond
mesh_terms: D001930:Brain Injuries / Q000503:physiopathology*; D019992:Databases as Topic; D004185:Disability Evaluation; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D016571:Neural Networks, Computer; D017063:Outcome Assessment, Health Care / Q000379:methods*; D012044:Regression Analysis; D020379:Risk Adjustment