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摘要翻译：
目标是开发一种新的方法，用于心脏病预测和诊断使用智能代理。最初，症状是用基于过滤器和包装器的代理进行预处理的。过滤器去除缺失的或不相关的症状。包装器用于根据阈值限制提取数据集中的数据。每个症状的依赖性使用依赖性检查代理来识别。分类是基于症状的先验概率和后验概率与证据值。最后将症状分为无症状、开始症状、轻度症状、中度症状和重度症状五类。利用合作方法解决了心脏问题，并对其进行了验证。
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英文标题：
《A Novel Approach for Cardiac Disease Prediction and Classification Using
Intelligent Agents》
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作者：
Murugesan Kuttikrishnan
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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：Multiagent Systems 多智能体系统
分类描述：Covers multiagent systems, distributed artificial intelligence, intelligent agents, coordinated interactions. and practical applications. Roughly covers ACM Subject Class I.2.11.
涵盖多Agent系统、分布式人工智能、智能Agent、协调交互。和实际应用。大致涵盖ACM科目I.2.11类。
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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：
The goal is to develop a novel approach for cardiac disease prediction and diagnosis using intelligent agents. Initially the symptoms are preprocessed using filter and wrapper based agents. The filter removes the missing or irrelevant symptoms. Wrapper is used to extract the data in the data set according to the threshold limits. Dependency of each symptom is identified using dependency checker agent. The classification is based on the prior and posterior probability of the symptoms with the evidence value. Finally the symptoms are classified in to five classes namely absence, starting, mild, moderate and serious. Using the cooperative approach the cardiac problem is solved and verified.
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PDF链接：
https://arxiv.org/pdf/1009.5346
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