A Fuzzy Rule Based Approach to Predict Risk Level of Heart D

发布时间：2022-02-16 07:32

　　在21世纪,医疗保健系统要面对来自老人,小孩和青年人日益增长的心脏疾病的压力。在过去的几十年里,信息和通讯技术的发展有了令人难以置信的提高,特别是依附于ICT系统。ICT系统在用于新的医疗精华来源,医疗组织形式和全球经济建设上。基于Fuzzy原则系统在信息通讯技术上起到了重要的作用,医疗系统也在社会和经济发展上贡献了心血管疾病和现代医学的支持。然而,为了利用Fuzzy原则医疗企业和患者有必要根据Fuzzy原则来诊断系统的可靠性,性能和部署而开展医疗系统。现在就有很多文献中许多的研究人员和学者都是依靠Fuzzy原则的支持通过医疗领域的智能系统,机器人系统,医疗数据处理和分析来处理。但这些Fuzzy原则应该建立在对心血管疾病支持系统和需要进一步研究讨论上。同时,我们提出了基于Fuzzy原则对心血管病人更有效和高效性。在我们的系统里,我们绝对要最小化输入属性的数量和减少诊断测试的次数。我们使用7属性,6输入和一个输出结果来识别患者的心血管疾病。我们把6个重要症状,体征,属性输入到计算机数据中加入（年纪,血压,胆固醇,最大心率,历史峰值,铊扫描）和输出一个范围从0到1的风险值,例如：健康和生病... 

【文章来源】：中南大学湖南省211工程院校985工程院校教育部直属院校

【文章页数】：74 页

【学位级别】：硕士

【文章目录】：
ACKNOWLEDGEMENT
摘要
ABSTRACT
TABLE OF CONTENTS
LIST OF FIGURES
LIST OF TABLES
LIST OF ABBRIVATIONS
CHAPTER 1:INTRODUCTION
    1.1 Introduction
    1.2 Motivation
    1.3. Declaration of Problem
    1.4 Objective
        1.4.1 General Objective
        1.4.2 Specific Objective
    1.5 Relevant Work
    1.6 Fuzzy Logic and Cardiovascular Disease
        1.6.1 Fuzzy Logic
        1.6.2 Cardiovascular Disease
    1.7 Thesis Outline
CHAPTER 2:FUZZY LOGIC
    2.1 Introduction
    2.2 Fuzzy Logic
    2.3 Fuzzy Rules and Reasoning
        2.3.1 Fuzzy If-Then Rules
        2.3.2 Fuzzy Reasoning
            2.3.2.1 Approximation
            2.3.2.2 Realization
    2.4 Membership Functions
        2.4.1 Types of Membership Function
    2.5 Building Fuzzy Logic Model
        2.5.1 Input
        2.5.2 Fuzzification
        2.5.3 Inference Engine(Rule Base)
        2.5.4 Defuzzification
            2.5.4.1 Mean of Maximum(MOM)Method
            2.5.4.2 Centre of Area/Gravity(COG)Method
            2.5.4.3 Bisector of area(BOA)
        2.5.5 Output
    2.6 Advantages and Disadvantage of Fuzzy System
    2.7 Chapter summary
CHAPTER 3:CARDIOVASCULAR DISEASE AND METHODOLOGY
    3.1 Exactly what is cardiovascular disease
    3.2 Types of the Cardiovascular Disease
    3.3 Principal Symptoms of Cardiovascular disease
    3.4 Cardiovascular disease Diagnosis
        3.4.1 ECG
        3.4.2 Blood Tests
        3.4.3 Echocardiography(ECHO)
        3.4.4 Stress Test
    3.5 Treatments for Heart Disease
    3.6 Risk factors and ranges
    3.7 Diagnosis diseases methodology
    3.8 Systematic shape of Fuzzy Model
        3.8.1 Multi-Input Multi-Output
    3.9 Proposed Model of Fuzzy Rule Based system;for heart disease diagnose
    3.10 Chapter Summary
CHAPTER 4:PROPOSED SYSTEM AND IMPLEMENTATION
    4.1 Introduction
    4.2 Fuzzy Rule Based system for heart disease diagnose
    4.3 Description of heart disease datasets
    4.4 Data Processing
        4.4.1 Data Formats
        4.4.2 Attribute Selection
    4.5 Algorithm
    4.6 System Phases
        4.6.1 Input(Fuzzification)and Membership Function
        4.6.2 Rules evaluation
        4.6.3 Output(Defuzzifiction)
    4.7 Chapter Summary
CHAPTER 5:SYSTEM TESTING AND CONCLUSION
    5.1 System Testing
    5.2 Conclusion
    5.3 Summary
BIBLIOGRAPHY
ACHIEVEMENTS



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