毕业论文：《基于Rough_Set_辅助临床诊断系统的应用与研究》.docVIP

精品 摘　　要 随着计算机与网络信息技术的发展，医院的数字和网络化得到了快速的兴起，但医院数据库中仍有大量有价值的信息或蕴藏的知识还没有得到充分挖掘和利用,造成数据资源浪费。粗糙集理论作为一种较新的软计算方法，主要用于处理不确定性、不分明性和模糊性知识，其基本思想是在保持分类能力不变的前提下，通过知识约简，导出概念的分类规则，并从中发现隐含的知识，揭示出潜在的新知识和规律[1]。Rough Set在近年来越来越受到重视，并逐步成为数据挖掘领域的研究热点之一，在辅助临床诊断上得到充分的运用。 Rough Set辅助临床诊断系统是一个以粗糙集为理论基础，通过使用五种不同的方法对已经简约了专家确诊的信息表进行计算，检验计算的正确性，并以此确定阈值。然后，通过输入简单的病人症状信息，从而得出对病人病情的确诊单。 关键词：粗糙集；粗糙包含；诊断规则；辅助诊断；糖尿病；学习；测试；诊断 ABSTRACT With the development of computer and network IT, digital and network of hospitals has been a rapid rise of a lot of valuable information or hidden knowledge has not yet been fully exploit the waste of data resources, but still in the hospital database. Rough set theory as a relatively new soft computing method for dealing with uncertainty, not clear and fuzzy knowledge, the basic idea is the premise of maintaining the same classification ability, through knowledge reduction, export the concept classification rules, and to find hidden knowledge, and reveal the potential of new knowledge and the law. On Rough Set in recent years more and more attention, and gradually become one of the hot research field of data mining, been fully used in assisted clinical diagnosis. Rough Set-assisted clinical diagnosis system is a rough set-theoretical foundation, have been simple expert confirmed information table is calculated by using five different methods to test the correctness of the calculation, and to determine the threshold Then, by entering simple information of the patients symptoms to arrive at a single diagnosis on the patients condition.Key words: Rough set; Rough contains; Diagnosis rules; Assistant diagnosis; Diabetes; learning; testing; diagnosis 目 录 TOC \o 1-3 \h \u 摘　　要 h I ABSTRACT h II 第1章　绪论 h 1 1.1　概述 h 1 第2章　粗糙集理论 h 2 2.1 粗糙集理论提出的背景 h 2 2.2 粗糙集理论的发展历史 h 2 2.3 粗糙集的主要优势 h 3 2.4 粗糙集研究方向 h 3 2.5 粗糙集的定义 h 4 2.5.1 信息系统 h 4 2.5.2 属性约简 h 4 2.5.3 准确度和覆盖 h 6 2.5.4 可能性规则 h 6 2.5.5 特征化 h 6 2.5.6 粗糙包含