基于信息熵的决策树在慢性胃炎中医辨证中的应用

目的:探讨基于信息熵的决策树在慢性胃炎中医辨证分型中的应用.方法:采用bootstrap方法对406例样本进行扩增以满足数据挖掘对样本量的要求,采用基于信息熵的决策树C4.5算法建立中医辨证模型.结果:决策树C4.5算法筛选出对中医辨证分型有意义的26个因素并对其重要性进行排序;产生清楚易懂可用于分类的决策规则;建立辨证模型,模型分类符合率为:训练集83.60%,验证集80.67%,测试集81.25%;模型区分各类证型的灵敏度和特异度也较高.结论:决策树C4.5算法建立的模型效果较好,可应用于慢性胃炎中医证型的鉴别诊断.     

基于极值随机森林的慢性胃炎中医证候分类

大多数机器学习算法能得到较好的分类效果,但模型却无法解释;而随机森林等模型有良好的可解释性,却无法处理中医数据中兼证的情况。本文利用极值随机森林算法对慢性胃炎中医数据进行证候分类研究,其中决策树的叶节点能输出多个标签,通过加权机制综合分量来处理兼证问题。与已有多标记学习算法和C4.5、CART等基于决策树的算法进行比较,实验结果表明,极值随机森林算法无论在6个证型的分类准确率上,还是在多标记评价指标上都具有更好的效果,而且模型中得到的规则基本符合中医理论。     

中医辨证分型治疗慢性胃炎的临床研究

目的：探讨中医辨证分型对于治疗慢性胃炎的临床疗效。方法：随机选取本院的200例慢性胃炎患者,以其完整临床资料为研究依据,所有患者根据中医辨证分型后采取对症治疗。结果：针对不同的中医辨证分型,采取不同的治疗方法,大部分患者病情都有所好转,症状明显减轻。其中慢性浅表性胃炎（CSG）共138例,辨证分型以肝胃气滞型为主,共100例（占72．5％）;慢性萎缩性胃炎（CAG）共62例,辨证分型以脾胃虚寒和胃阴不足型为主（各占40．3％和32．3％）。结论：临床上采用中医辨证分型治疗慢性胃炎时应审证求因,辨证论治,通过清脾泻热、健脾和中、疏肝理气、养阴益胃、活血化瘀等中医治则治法,疗效确切。     

慢性胃炎的辨证施护

慢性胃炎是常见的消化道疾病，属中医“胃院痛”范畴，我们依据慢性胃炎证型进行施护。1临床资料男性20例，女性10例，年龄在30～60岁、经胃镜检查浅表性胃炎25例，其中3例伴幽门螺旋菌感染;萎缩性胃炎5例，其中1例伴肠上皮化生。临床表现：胃院部不适，餐后上腹隐痛，闷胀，胃纳欠佳。2心理特点因“胃脘痛”症状反复出现，老年患者产生焦虑，尤其是萎缩性胃炎，肠上度化生者担心变成胃癌，存在恐惧心理。应给予患者以精神上安慰，细心讲授胃炎的知识，使病者树立信心，坚持治疗。3辨证施护慢性胃炎中医分7种症型，对不同的证型有不同的辨证…     

基于医案数据研究萎缩性胃炎的辨证及组方规律

目的 通过研究慢性萎缩性胃炎的中医医案,总结整理出中医治疗慢性萎缩性胃炎的辨证以及组方规律。方法 收集治疗慢性萎缩性胃炎的相关中医医案,运用数据分析法、聚类算法以及关联规则分析等多种研究方法,整理有效数据并总结概括出中医治疗慢性萎缩性胃炎的辨证和组方用药规律。结果 本研究通过分析252份萎缩性胃炎的相关中医医案,对医案中常见的证候、具体治法、使用较高频次的中药及药物配伍间的关联规则高度概括,最终得出32个核心配伍及14个新处方。结论 中医治疗慢性萎缩性胃炎在证型、具体治法、治疗用药等多个方面有一定规律可循,因此,借助转化医学的分析方法和医案数据挖掘技术得出的萎缩性胃炎的治疗规律具有一定的可行性及临床参考价值。     

中医证候研究中的分类算法方法学研究

中医证的研究一直是中医药现代化研究的关键之一,其核心是证候分类和诊断标准的研究,数据挖掘中的分类算法已经大量应用于中医证候的分类研究。本文评述了数据挖掘中分类算法在中医证候研究中的应用,对其中主要算法的特点、适用条件和范围进行综合分析,认为应该根据不同的研究目的,选择适当的分类算法。粗糙集和聚类分析不需要先验知识,适合进行探索性的研究;模糊集理论、神经网络和决策树需要先验知识,适合应用于分类目标比较明确的证候诊断标准研究;模糊集理论更适合与其他分类算法结合应用,产生模糊聚类、模糊神经网络、模糊粗糙集和模糊决策树等更适合中医证候分类研究的算法。在具体的辨证分类研究中,我们需要根据所研究的疾病和证型分类特点选择合适的分类算法及其组合,同时建议应该在集成多学科理论与技术的基础上进行创新,建立符合中医证候特点的分类算法。     

胃粘膜血流改变与慢性胃病中医辨证关系的研究

目的 :探讨胃粘膜血流量与慢性胃病中医辨证的关系。方法 :对慢性浅表性胃炎、慢性萎缩性胃炎以及门脉高压性胃病三组患者进行辨证分析 ,用激光多普勒仪检测胃粘膜血流量值 ,分析三组患者胃粘膜血流量值与中医辨证的相关性。结果 :慢性浅表性胃炎组胃粘膜血流量值 ( 32 8.5 2±5 1 .5 8) ml/min,慢性萎缩性胃炎 ( 2 70 .0 9± 5 9.2 8) ml/min,门脉高压性胃病组 ( 2 5 6.60± 71 .5 6) ml/min。三组胃粘膜血流量值差异有非常显著性意义 ,P<0 .0 1。结论 :胃粘膜血流量与中医辨证关系密切 ,检测胃粘膜血流量值有助于指导慢性胃炎的中医辨证与治疗。     

慢性胃炎中医证型与内镜分类的相关性研究

目的研究慢性胃炎中医证型与内镜分类的相关性。方法对2007年9月～2008年9月就诊于消化内科接受胃镜检查的病例,进行中医证型与内镜分类。结果 222例慢性胃炎患者内镜分类差异有显著性意义（p〈0.01）,以平坦糜烂性胃炎和红斑渗出性胃炎为多,各种中医证型中除胃络淤阻型以外,其余5种证型与内镜分类的关系,采用非参数χ2检验,差异均有统计学意义（p〈0.01或p〈0.05）。结论慢性胃黏膜的病理变化随着胃黏膜炎症的加重而加重,病情由轻转重,病性由实转虚,是一个逐渐演变加重的病理过程。提出慢性胃炎的不同中医证型的胃镜诊断标准,为防治胃黏膜疾病提供理论依据。     

决策树算法在医院数据挖掘中的应用探索

介绍决策树的基本原理,对决策树算法在医院信息系统中的应用进行研究,以肝癌为例对医院临床数据进行挖掘,经过数据预处理,应用ID3算法建立完整的决策树.用测试数据测试,该决策树具有很高的准确率,指出决策树算法在医院信息系统中具有广泛的应用前景.     

李飞泽运用香砂六君子汤治疗慢性胃炎经验

李飞泽是浙江省名中医,第六批全国老中医药专家学术继承指导老师,从事中医临床及科研30年,学验俱丰。擅长运用中医、中西医结合的方法治疗内科疑难杂症,临床诊治慢性胃炎尤具特色,辨证准确,用药精当,疗效颇佳。笔者有幸侍诊,现将其经验总结如下。1病因病机慢性胃炎临床分为慢性萎缩性胃炎和慢性非萎缩性胃炎,幽门螺杆菌(Hp)感染是其最主要病因,此外,尚有胆汁反流、长期服用非甾体抗炎药(NSAID)等药物、乙醇摄入及自身免疫功能异常(自身免疫性胃炎)等。     

The diagnostic rules of peripheral lung cancer preliminary study based on data mining technique

Objective： To discuss the clinical and imaging diagnostic rules of peripheral lung cancer by data mining technique, and to explore new ideas in the diagnosis of peripheral lung cancer, and to obtain early-stage technology and knowledge support of computer-aided detecting （CAD）. Methods： 58 cases of peripheral lung cancer confirmed by clinical pathology were collected. The data were imported into the database after the standardization of the clinical and CT findings attributes were identified. The data was studied comparatively based on Association Rules （AR） of the knowledge discovery process and the Rough Set （RS） reduction algorithm and Genetic Algorithm（GA） of the generic data analysis tool （ROSETTA）, respectively. Results： The genetic classification algorithm of ROSETTA generates 5 000 or so diagnosis rules. The RS reduction algorithm of Johnson＇s Algorithm generates 51 diagnosis rules and the AR algorithm generates 123 diagnosis rules. Three data mining methods basically consider gender, age, cough, location, lobulation sign, shape, ground-glass density attributes as the main basis for the diagnosis of peripheral lung cancer. Conclusion： These diagnosis rules for peripheral lung cancer with three data mining technology is same as clinical diagnostic rules, and these rules also can be used to build the knowledge base of expert system. This study demonstrated the potential values of data mining technology in clinical imaging diagnosis and differential diagnosis.     

基于遗传算法的关联规则挖掘研究

对在传统的关联规则挖掘算法下产生的关联规则出现的问题进行分析,引入兴趣度并结合遗传算法的特点,提出一种基于遗传算法的关联规则挖掘算法,通过遗传算法的自适应寻优技术和兴趣度更好地筛选出关联规则。通过实验证明,该算法是有效的。     

A Novel Feature Level Fusion for Heart Rate Variability Classification Using Correntropy and Cauchy-Schwarz Divergence

Heart rate variability (HRV) analysis has become a widely used tool for monitoring pathological and psychological states in medical applications. In a typical classification problem, information fusion is a process whereby the effective combination of the data can achieve a more accurate system. The purpose of this article was to provide an accurate algorithm for classifying HRV signals in various psychological states. Therefore, a novel feature level fusion approach was proposed. First, using the theory of information, two similarity indicators of the signal were extracted, including correntropy and Cauchy-Schwarz divergence. Applying probabilistic neural network (PNN) and k-nearest neighbor (kNN), the performance of each index in the classification of meditators and non-meditators HRV signals was appraised. Then, three fusion rules, including division, product, and weighted sum rules were used to combine the information of both similarity measures. For the first time, we propose an algorithm to define the weights of each feature based on the statistical p-values. The performance of HRV classification using combined features was compared with the non-combined features. Totally, the accuracy of 100% was obtained for discriminating all states. The results showed the strong ability and proficiency of division and weighted sum rules in the improvement of the classifier accuracies.     

Fuzzy Expert System based on a Novel Hybrid Stem Cell (HSC) Algorithm for Classification of Micro Array Data

In the growing scenario, microarray data is extensively used since it provides a more comprehensive understanding of genetic variants among diseases. As the gene expression samples have high dimensionality it becomes tedious to analyze the samples manually. Hence an automated system is needed to analyze these samples. The fuzzy expert system offers a clear classification when compared to the machine learning and statistical methodologies. In fuzzy classification, knowledge acquisition would be a major concern. Despite several existing approaches for knowledge acquisition much effort is necessary to enhance the learning process. This paper proposes an innovative Hybrid Stem Cell (HSC) algorithm that utilizes Ant Colony optimization and Stem Cell algorithm for designing fuzzy classification system to extract the informative rules to form the membership functions from the microarray dataset. The HSC algorithm uses a novel Adaptive Stem Cell Optimization (ASCO) to improve the points of membership function and Ant Colony Optimization to produce the near optimum rule set. In order to extract the most informative genes from the large microarray dataset a method called Mutual Information is used. The performance results of the proposed technique evaluated using the five microarray datasets are simulated. These results prove that the proposed Hybrid Stem Cell (HSC) algorithm produces a precise fuzzy system than the existing methodologies.     

曲前列环素对大鼠肺动脉高压模型的治疗作用及其机制

目的: 研究曲前列环素对大鼠肺动脉高压的疗效及其对肺组织分化抑制因子（inhibitor of differentiation,ID）1、3表达水平的影响。方法: 建立大鼠野百合碱肺动脉高压模型,设模型组、干预组、对照组,每组10只。干预组在模型大鼠背部微泵注射曲前列环素2周,模型组和对照组给予等量生理盐水。测定各组大鼠右心室平均压（mRVP）;称量心脏各部分重量,计算右心室肥厚指数（RVHI）;制作肺组织切片并进行HE染色,测定肺小动脉管壁厚度与动脉外径的百分比（WT）及血管壁面积与血管总截面积的百分比（WA）。免疫组织化学法测定肺血管ID1、ID3的表达;蛋白质印迹法测定肺组织ID1、ID3含量;实时荧光定量PCR 检测肺组织ID1 mRNA、ID3 mRNA的表达量。结果： 模型组和干预组mRVP、RVHI、WT、WA均明显高于对照组（均P<0.05）,干预组上述指标明显低于模型组（P<0.05）。模型组肺血管和肺组织ID1、ID3及肺组织ID1 mRNA、ID3 mRNA的表达量明显低于对照组(均P<0.05),而干预组明显高于模型组(均P<0.05)。结论： 曲前列环素能促进野百合碱诱导的肺动脉高压大鼠肺组织ID1、ID3及ID1 mRNA、ID3 mRNA的表达,对大鼠肺动脉高压有治疗作用。     

Design of a Fuzzy-based Decision Support System for Coronary Heart Disease Diagnosis

In the present paper, a fuzzy rule-based system (FRBS) is designed to serve as a decision support system for Coronary heart disease (CHD) diagnosis that not only considers the decision accuracy of the rules but also their transparency at the same time. To achieve the two above mentioned objectives, we apply a multi-objective genetic algorithm to optimize both the accuracy and transparency of the FRBS. In addition and to help assess the certainty and the importance of each rule by the physician, an extended format of fuzzy rules that incorporates the degree of decision certainty and importance or support of each rule at the consequent part of the rules is introduced. Furthermore, a new way for employing Ensemble Classifiers Strategy (ECS) method is proposed to enhance the classification ability of the FRBS. The results show that the generated rules are humanly understandable while their accuracy compared favorably with other benchmark classification methods. In addition, the produced FRBS is able to identify the uncertainty cases so that the physician can give a special consideration to deal with them and this will result in a better management of efforts and tasks. Furthermore, employing ECS has specifically improved the ability of FRBS to detect patients with CHD which is desirable feature for any CHD diagnosis system.     

基于迁移学习的全连接神经网络舌象分类方法

目的 针对深度学习在舌象分类中训练数据量大、训练设备要求高、训练时间长等问题,提出一种基于迁移学习的全连接神经网络小样本舌象分类方法。方法 应用经ImageNet海量数据集训练后的卷积Inception_v3网络提取舌象点、线等有效特征,再使用全连接神经网络对特征进行训练分类,将深度学习网络学习到的图像知识迁移到舌象识别任务中。利用舌象数据集进行训练、测试。结果 与典型舌象分类方法K最近邻（KNN）算法、支持向量机（SVM）算法和卷积神经网络（CNN）深度学习方法相比,本实验使用的两种方法（Inception_v3+2NN和Inception_v3+3NN）具有较高的舌象分类识别率,准确率分别达90.30%和93.98%,且样本训练时间明显缩短。结论 与KNN算法、SVM算法和CNN深度学习方法相比,基于迁移学习的全连接神经网络舌象分类方法可有效提高舌象分类的准确率、缩短网络的训练时间。     

基于决策树分类技术的大肠早癌诊断系统研究

研究和开发一种基于数据挖掘技术的大肠早癌诊断系统.该系统首先对所采集的大量激光诱导自体荧光光谱进行处理,并建立相关数据库,然后采用决策树分类方法对样本进行训练和分类,最终进行正常组织和癌变组织的判断,并由系统输出诊断结果.结果表明该系统可有效地用于指导大肠癌症的早期诊断和治疗.