title: Performance of an artificial neural network for vertical root fracture detection: an ex vivo study.
abstract: OBJECTIVE
  To develop an artificial neural network for vertical root fracture detection.
  
  
  METHODS
  A probabilistic neural network design was used to clarify whether a tooth root was sound or had a vertical root fracture. Two hundred images (50 sound and 150 vertical root fractures) derived from digital radiography--used to train and test the artificial neural network--were divided into three groups according to the number of training and test data sets: 80/120,105/95 and 130/70, respectively. Either training or tested data were evaluated using grey-scale data per line passing through the root. These data were normalized to reduce the grey-scale variance and fed as input data of the neural network. The variance of function in recognition data was calculated between 0 and 1 to select the best performance of neural network. The performance of the neural network was evaluated using a diagnostic test.
  
  
  RESULTS
  After testing data under several variances of function, we found the highest sensitivity (98%), specificity (90.5%) and accuracy (95.7%) occurred in Group three, for which the variance of function in recognition data was between 0.025 and 0.005.
  
  
  CONCLUSIONS
  The neural network designed in this study has sufficient sensitivity, specificity and accuracy to be a model for vertical root fracture detection.
authors.affiliation: Department of Oral Diagnosis, Faculty of Dentistry, Khon Kaen University, Khon Kaen, Thailand. suwadee@kku.ac.th
authors.forename: Suwadee
authors.initials: S
authors.lastname: Kositbowornchai
authors.forename: Supattra
authors.initials: S
authors.lastname: Plermkamon
authors.forename: Tawan
authors.initials: T
authors.lastname: Tangkosol
mesh_terms: D006801:Humans; D016571:Neural Networks, Computer; D011857:Radiographic Image Interpretation, Computer-Assisted; D019252:Radiography, Dental, Digital / Q000379:methods*; D012680:Sensitivity and Specificity; D012985:Software Design; D014082:Tooth Fractures / Q000000981:diagnostic imaging*; D014092:Tooth Root / Q000000981:diagnostic imaging*