Podgorelec Vili, Kokol Peter, Stiglic Bruno, Rozman Ivan
University of Maribor - FERI, Slovenia.
J Med Syst. 2002 Oct;26(5):445-63. doi: 10.1023/a:1016409317640.
In medical decision making (classification, diagnosing, etc.) there are many situations where decision must be made effectively and reliably. Conceptual simple decision making models with the possibility of automatic learning are the most appropriate for performing such tasks. Decision trees are a reliable and effective decision making technique that provide high classification accuracy with a simple representation of gathered knowledge and they have been used in different areas of medical decision making. In the paper we present the basic characteristics of decision trees and the successful alternatives to the traditional induction approach with the emphasis on existing and possible future applications in medicine.
在医疗决策(分类、诊断等)中,存在许多必须有效且可靠地做出决策的情况。具有自动学习可能性的概念简单的决策模型最适合执行此类任务。决策树是一种可靠且有效的决策技术,它以简单的方式表示所收集的知识,从而提供高分类准确率,并且已被用于医疗决策的不同领域。在本文中,我们介绍了决策树的基本特征以及传统归纳方法的成功替代方法,重点是医学领域中现有的和可能的未来应用。