从异构医疗数据存储库进行分布式数据挖掘:迈向基于智能代理的框架

S. Zaidi, S. Abidi, S. Manickam
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引用次数: 21

摘要

本文介绍了在包含多个异构医疗数据存储库的分布式医疗环境中用于知识发现的基于智能代理的框架的一个案例。以数据为中介的知识发现,特别是来自多个异构数据资源的知识发现,是一个繁琐的过程,并对最终用户施加了重大的操作限制。我们证明,自主的、被动的和主动的智能代理为医疗保健专业人员和管理人员提供了生成面向最终用户的、打包的、增值的决策支持/战略规划服务的机会。我们建议使用智能代理来实现基于分布式代理的数据挖掘信息结构,该结构提供了一套面向医疗保健的决策支持/战略规划服务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed data mining from heterogeneous healthcare data repositories: towards an intelligent agent-based framework
This paper presents a case for an intelligent agent-based framework for knowledge discovery in a distributed healthcare environment comprising multiple heterogeneous healthcare data repositories. Data-mediated knowledge discovery, especially from multiple heterogeneous data resources, is a tedious process and imposes significant operational constraints on end-users. We demonstrate that autonomous, reactive and proactive intelligent agents provide an opportunity to generate end-user-oriented, packaged, value-added decision-support/strategic planning services for healthcare professionals and managers. We propose the use of intelligent agents to implement a distributed agent-based data mining information structure that provides a suite of healthcare-oriented decision-support/strategic planning services.
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