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摘要翻译：
本文介绍了一种基于案例推理的急性细菌性脑膜炎医学诊断系统的研究结果。研究了适应阶段的实现，从案例推理和规则专家系统的集成两个方面进行了研究。在这个适应阶段，我们使用更高级别的RBC，它存储并允许重用更改经验，并结合经典的基于规则的推理引擎。为了考虑到最明显的临床情况，使用规则引擎实现诊断前阶段，该规则引擎给定明显的情况，发出相应的诊断并避免整个过程。
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英文标题：
《Integration of Rule Based Expert Systems and Case Based Reasoning in an
Acute Bacterial Meningitis Clinical Decision Support System》
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作者：
Mariana Maceiras Cabrera, Ernesto Ocampo Edye
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最新提交年份：
2010
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分类信息：
一级分类：Computer Science 计算机科学
二级分类：Artificial Intelligence 人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
This article presents the results of the research carried out on the development of a medical diagnostic system applied to the Acute Bacterial Meningitis, using the Case Based Reasoning methodology. The research was focused on the implementation of the adaptation stage, from the integration of Case Based Reasoning and Rule Based Expert Systems. In this adaptation stage we use a higher level RBC that stores and allows reutilizing change experiences, combined with a classic rule-based inference engine. In order to take into account the most evident clinical situation, a pre-diagnosis stage is implemented using a rule engine that, given an evident situation, emits the corresponding diagnosis and avoids the complete process.
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PDF链接：
https://arxiv.org/pdf/1003.1493
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