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Acad Radiol. 2005 Apr;12(4):415-21.

Development of radiology prediction models using feature analysis.

Author information

1
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

Abstract

RATIONALE AND OBJECTIVES:

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.

MATERIALS AND 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.

PMID:
15831414
DOI:
10.1016/j.acra.2005.01.009
[Indexed for MEDLINE]

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