title: Development of radiology prediction models using feature analysis.
abstract: OBJECTIVE
  This article provides an introduction to prediction models and their application in diagnostic imaging research. Prediction models capitalize on the different degrees of association among variables to make a prediction of a health state, formulate a rule, or quantify individual contributions of various predictor variables. The purpose of this article is to elucidate the rationale, implication, and interpretation of prediction models using imaging features.
  
  
  METHODS
  The techniques and challenges of developing, testing, and implementing prediction models are described. Prediction model development methods are similar to data-mining techniques.
  
  
  RESULTS
  Learning objectives are to review prediction rule (model) methods, learn how prediction models may be applied to feature analysis, and understand the challenges of developing, testing, and implementing prediction models.
authors.affiliation: Magnetic Resonance Therapy Program, Spine Intervention Service, and Department of Radiology, Brigham and Women's Hospital, ASB-1, L1, Rm 003A, 75 Francis St, Boston, MA 02115, USA. jcarrino@partners.org
authors.forename: John A
authors.initials: JA
authors.lastname: Carrino
authors.forename: Lucila
authors.initials: L
authors.lastname: Ohno-Machado
mesh_terms: D003661:Decision Support Techniques; D005544:Forecasting / Q000379:methods*; D006801:Humans; D011237:Predictive Value of Tests; D011871:Radiology / Q000592:standards / Q000639:trends*