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eXiT~*CBR.v2: Distributed case-based reasoning tool for medical prognosis

机译:eXiT〜* CBR.v2:用于医学预后的基于案例的分布式推理工具

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摘要

In this work we propose a user-friendly medically oriented tool for prognosis development systems and experimentation under a case-based reasoning methodology. The tool enables health care collaboration practice to be mapped in cases where different doctors share their expertise, for example, or where medical committee composed of specialists from different fields work together to achieve a final prognosis. Each agent with a different piece of knowledge classifies the given cases through metrics designed for this purpose. Since multiple solutions for the same case are useless, agents collaborate among themselves in order to achieve a final decision through a coordinated schema. For this purpose, the tool provides a weighted voting schema and an evolutionary algorithm (genetic algorithm) to learn robust weights. Moreover, to test the experiments, the tool includes stratified cross-validation methods which take the collaborative environment into account. In this paper the different collaborative facilities offered by the tool are described. A sample usage of the tool is also provided.
机译:在这项工作中,我们为基于案例推理方法的预后开发系统和实验提出了一种用户友好的面向医学的工具。例如,在不同医生分享其专业知识的情况下,或由来自不同领域的专家组成的医学委员会共同努力以实现最终预后的情况下,该工具可使医疗保健协作实践得到映射。具有不同知识的每个代理都通过为此目的设计的指标对给定案例进行分类。由于针对同一案例的多种解决方案是无用的,因此代理之间必须进行协作,以便通过协调的方案达成最终决策。为此,该工具提供了一个加权投票方案和一个进化算法(遗传算法)来学习鲁棒的权重。此外,为了测试实验,该工具包括分层的交叉验证方法,该方法考虑了协作环境。本文描述了该工具提供的不同协作工具。还提供了该工具的示例用法。

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