Use of the C4.5 machine learning algorithm to test a clinical guideline-based decision support system. - Archive ouverte HAL Access content directly
Journal Articles Studies in Health Technology and Informatics Year : 2008

Use of the C4.5 machine learning algorithm to test a clinical guideline-based decision support system.

Abstract

Well-designed medical decision support system (DSS) have been shown to improve health care quality. However, before they can be used in real clinical situations, these systems must be extensively tested, to ensure that they conform to the clinical guidelines (CG) on which they are based. Existing methods cannot be used for the systematic testing of all possible test cases. We describe here a new exhaustive dynamic verification method. In this method, the DSS is considered to be a black box, and the Quinlan C4.5 algorithm is used to build a decision tree from an exhaustive set of DSS input vectors and outputs. This method was successfully used for the testing of a medical DSS relating to chronic diseases: the ASTI critiquing module for type 2 diabetes.
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Dates and versions

hal-00912885 , version 1 (02-12-2013)

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Jean-Baptiste Lamy, Anis Ellini, Vahid Ebrahiminia, Jean-Daniel Zucker, Hector Falcoff, et al.. Use of the C4.5 machine learning algorithm to test a clinical guideline-based decision support system.. Studies in Health Technology and Informatics, 2008, 136, pp.223-8. ⟨hal-00912885⟩
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