本文選題：冠心病　切入點：早期預警系統(tǒng)　出處：《河北大學》2017年碩士論文

【摘要】：隨著經濟社會的快速發(fā)展,在生活水平提高的同時生活節(jié)奏也大大加快,診療技術的發(fā)展卻相對滯后,冠心病是目前威脅人類健康的主要疾病之一。但是往往由于人們工作的繁忙、醫(yī)療費用的昂貴、醫(yī)生的缺少,使得很多人無法及時發(fā)現病情,貽誤了最佳治療時機。本論文是從具有多年臨床經驗的心內科醫(yī)生所提供的、日常生活中能夠容易獲得的個人生理屬性的大量數據中,運用數據挖掘技術得到生理屬性的各參數間潛在的、有價值的規(guī)則,并且把這些規(guī)則應用到冠心病早期預警系統(tǒng)之中。該系統(tǒng)對于冠心病的早期預防和診治具有重要意義。論文主要研究內容如下:1.從某三甲醫(yī)院收集了大量冠心病患者病歷和某高校學生家庭成員健康問卷調查表得到的健康人群的數據,并進行了數據整理,作為算法訓練的樣本。2.給出了一個基于BP神經網絡的冠心病判別算法,目標就是通過測試者的各項屬性值來判斷其是否可能患有冠心病。首先,通過樣本進行訓練,設計網絡模型結構,得到一個相對較好的神經網絡模型。其次,根據生成的模型,計算出測試者是否有可能患有冠心病。3.使用樸素貝葉斯分析方法來預測患有冠心病的概率。分為兩個步驟:第一步,計算各項屬性不同取值的先驗概率;第二步,根據測試者的輸入信息,計算出患病概率。4.設計實現了冠心病預警原型系統(tǒng)。主要由兩部分組成,第一部分是人機接口部分,用于輸入預警系統(tǒng)所需要的個人身體狀況的基礎信息,并進行數據的完整性判斷。第二部分是系統(tǒng)對冠心病的預測部分,根據輸入的基本信息預測出冠心病的患病情況及健康建議。5.通過算法實驗和軟件系統(tǒng)測試,驗證了原型系統(tǒng)的有效性。使用本系統(tǒng),可以隨時根據自身情況來評估患病的風險,可以讓測試者保持警惕,積極調解自身狀態(tài),還可以為醫(yī)療機構的診斷提供有價值的參考。
[Abstract]:With the rapid development of economy and society, the pace of life has been greatly accelerated while the standard of living has been improved, while the development of diagnosis and treatment technology has lagged behind. Coronary heart disease (CHD) is one of the main diseases threatening human health at present. However, due to the busy work of people, the high cost of medical treatment and the lack of doctors, many people are unable to detect the disease in time. This paper is based on a wealth of data from cardiologists with many years of clinical experience who can easily obtain personal physiological properties in their daily lives. Using data mining technology to get potential and valuable rules between the parameters of physiological attributes, These rules are applied to the early warning system of coronary heart disease. This system is of great significance for the early prevention and treatment of coronary heart disease. The main contents of this paper are as follows: 1. A large number of coronary heart disease has been collected from a third class hospital. Patients' medical records and the data of healthy people obtained from a questionnaire on the health of family members of a college student, As a training sample of algorithm. 2. A BP neural network based coronary heart disease discrimination algorithm is presented. The goal is to determine whether the person is likely to have coronary heart disease through each attribute value of the tester. First of all, Through the training of samples, the network model structure is designed, and a relatively good neural network model is obtained. Secondly, according to the generated model, Use naive Bayesian analysis to predict the probability of coronary heart disease. There are two steps: the first step is to calculate the priori probability of different values of each attribute; the second step is to predict the probability of coronary heart disease. According to the input information of the tester, the probability of disease is calculated. 4. The prototype system of coronary heart disease warning is designed and implemented. The system is composed of two parts, the first part is the man-machine interface. It is used to input the basic information of the individual's physical condition needed by the early warning system and to judge the integrity of the data. The second part is the system's prediction of coronary heart disease. Based on the input of basic information to predict the prevalence of coronary heart disease and health advice .5.Through algorithm experiments and software system tests, the effectiveness of the prototype system is verified. Using this system, the risk of the disease can be assessed at any time according to their own conditions. It can keep the testers alert, actively mediate their own status, and can provide valuable reference for the diagnosis of medical institutions.
【學位授予單位】：河北大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R541.4;TP311.13

【參考文獻】

相關期刊論文 前10條

1 常青;;基于人工神經網絡的數學模型的建立策略探究[J];當代教育實踐與教學研究;2016年05期

2 王逸夫;李川;;基于數據挖掘的臨床醫(yī)學研究系統(tǒng)的設計與實現[J];四川生理科學雜志;2016年02期

3 秦文哲;陳進;董力;;大數據背景下醫(yī)學數據挖掘的研究進展及應用[J];中國胸心血管外科臨床雜志;2016年01期

4 甘昕艷;潘家英;梁京章;;數據挖掘技術在高血壓病種上的應用研究[J];電腦知識與技術;2015年05期

5 楊良斌;;數據挖掘領域研究現狀與趨勢的可視化分析[J];圖書情報工作;2015年S2期

6 邵峰峰;;數據挖掘技術在心臟病診斷建模中的應用研究[J];福建電腦;2015年02期

7 趙甲;;利用條件概率與乘法公式解釋搜索引擎拼寫糾錯功能的原理[J];湖北科技學院學報;2013年03期

8 黃宇達;王迤冉;;基于樸素貝葉斯與ID3算法的決策樹分類[J];計算機工程;2012年14期

9 王寅同;高如家;吳海飛;;醫(yī)學數據挖掘過程的研究[J];軟件工程師;2011年08期

10 張春英;王晶;;一種新型加權樸素貝葉斯分類算法[J];微計算機信息;2010年30期

相關碩士學位論文 前2條

1 梁耀波;智能醫(yī)療診斷系統(tǒng)的研究與實現[D];北京理工大學;2016年

2 趙長勇;面向智慧醫(yī)療的診斷信息數據挖掘應用研究[D];浙江大學;2014年

，

本文編號：1680735