基于关联规则和熵聚类的中医经方治疗抑郁症用药规律

目的:基于中医传承辅助平台(V2.5)软件,探讨中医经方治疗抑郁症的用药规律。方法:收集中国期刊全文数据库(CNKI),中文科技期刊数据库(VIP)和万方数据库发表的中医经方及其化裁治疗抑郁症的文献资料,时间设定为1986年1月至2016年12月,将所得数据规范完成后,输入中医传承辅助平台(V2.5)软件,建立数据库,运用中医传承辅助系统中的关联规则、改进的互信息法以及复杂系统熵聚类等无监督数据挖掘方法,分析治疗抑郁症经方中常用的药物、核心组合及发现新方。结果:筛选出符合条件的运用中医经方治疗抑郁症的发表文献共461篇,其中包含119首方剂,涉及中药155味,对其进行分析,发现方剂中出现有35味中药高频应用,频次前5位的中药为炙甘草、大枣、柴胡、半夏、白芍。通过关联规则挖掘出核心组合25个,通过聚类分析得到新方3个。结论:通过中医传承辅助平台(V2.5)对治疗抑郁症的中医经方进行分析,发现运用中医经方治疗抑郁症用药频次较高的中药,大多为辛甘温之品,归经于心、脾胃、肝、肾经的药物频率明显较高,其中尤以入心经为最多,这些高频中药大多有益气健脾、宁心安神、行气解郁的功效。经方治疗抑郁症注重通阳气、养心气、疏肝气、健脾气,为临床辨治抑郁症提供了参考。     

HPLC测定不同产地砂仁中原儿茶酸和香草酸的含量

目的:建立高效液相色谱法(HPLC)同时测定砂仁中原儿茶酸和香草酸的含量,并对不同产地砂仁的原儿茶酸和香草酸含量进行比较。方法:采用Phenomenex Luna C_(18)色谱柱(4.6 mm×250 mm,5μm),以甲醇-0.1%甲酸水为统计相进行梯度洗脱,柱温35℃,流速0.8 mL·min~(-1),进样体积15μL,检测波长260 nm。结果:原儿茶酸在0.000 7~0.008 9 g·L~(-1)呈良好的线性关系,平均回收率100.4%(RSD 3.2%);香草酸在0.000 6~0.030 3 g·L~(-1)呈良好的线性关系,平均回收率99.3%(RSD 2.8%)。对24批不同产地砂仁样品的原儿茶酸及香草酸含量测定结果进行聚类分析,结果显示不同产地砂仁样品分为两大类,一类为阳春砂与绿壳砂,另一类为进口壳砂仁、艳山姜伪品及加工方式为生晒的云南产阳春砂。结论:该方法简便、准确、重复性好,可用于不同产地砂仁中原儿茶酸和香草酸含量测定,为鉴别不同产地的砂仁样品提供参考。砂仁中香草酸含量受其加工方式影响含量变化明显。     

A two-step approach for mining patient treatment pathways in administrative healthcare databases

Clustering electronic medical records allows the discovery of information on healthcare practices. Entries in such medical records are usually composed of a succession of diagnostics or therapeutic steps. The corresponding processes are complex and heterogeneous since they depend on medical knowledge integrating clinical guidelines, the physician's individual experience, and patient data and conditions. To analyze such data, we are first proposing to cluster medical visits, consultations, and hospital stays into homogeneous groups, and then to construct higher-level patient treatment pathways over these different groups. These pathways are then also clustered to distill typical pathways, enabling interpretation of clusters by experts. This approach is evaluated on a real-world administrative database of elderly people in Québec suffering from heart failures.     

上海医学影像杂志2002年(第11卷)总目录

头颈部MRI测量诊断橄榄一桥脑一小脑萎缩················································……肖慧,胡万鹏,孙实香等(24)出血性脑中风CT表现与脑出血性碎死关系的logistiC回归分析·····················……柯棋,周守国,张红军(26)甲状腺良恶性肿瘤的超声鉴别诊断价值·······································································,…陈丽莉(68)新生儿缺氧缺血性脑病的CT…     

Computer aided analysis of breast MRI enhancement kinetics using mean shift c lustering and multifeature iterative region of interest selection

Purpose:

To evaluate automatic characterization of a breast MR lesion by its spatially coherent region of interest (ROI).

Materials and Methods:

The method delineated 247 enhancing lesions using Otsu thresholding after manually placing a sphere. Mean Shift Clustering subdivided each volume, based on features including pharmacokinetic parameters. An iteratively trained classifier to predict the most suspicious ROI (IsR) was used, to predict the malignancy likelihood of each lesion. Performance was evaluated using receiver operator characteristic (ROC) analysis, and compared with a previous prototype. IsR was compared with noniterative training. The effect of adding BI‐RADS? morphology (from a radiologist) to the classifier was investigated.

Results:

The area under the ROC curve (AUC) was 0.83 (95% confidence interval [CI] of 0.77–0.88), and was 0.75 (95%CI = 0.68–0.81; P = 0.029) without pharmacokinetic features. IsR performed better than conventional selection, based on one feature (AUC 0.75, 95%CI = 0.68–0.81; P = 0.035). With morphology, the AUC was 0.84 (95%CI = 0.78–0.88) versus 0.82 without (P = 0.40).

Conclusion:

Breast lesions can be characterized by their most suspicious, contiguous ROI using multi‐feature clustering and iterative training. Characterization was improved by including pharmacokinetic modeling, while in our experiments, including morphology did not improve characterization. J. Magn. Reson. Imaging 2012;36:1104–1112. © 2012 Wiley Periodicals, Inc.

     

基于互信息的失眠用药关联性分析

基于中医传承辅助系统软件,分析郭蓉娟教授治疗失眠的用药经验。收集郭蓉娟教授治疗失眠的中药方剂,采用关联规则apriori算法、改进的互信息算法、复杂系统熵聚类等无监督数据挖掘方法,确定处方中各种药物的使用频次及药物之间的关联规则,分析郭蓉娟教授治疗失眠的用药经验。对筛选出的3 084首处方进行分析,确定处方中药物的使用频次,药物之问的关联规则,挖掘出41个核心组合和7首新处方。结论符合郭教授对失眠病因病机的认识:以肝郁化火为核心病机,肝郁脾虚、久病及肾的特点,中医传承辅助系统对于挖掘名中医临床经验具有重要实用价值。     

丁元庆教授治疗抽动障碍用药规律的挖掘分析

近年来抽动障碍的发病有所增加,难治病例也不少见。西医发病原因和发病机制尚未明确,临床普遍使用的西药有诸多的不良反应,中医药研究越来越受到重视。该文基于中医传承辅助系统软件,探讨丁元庆教授治疗抽动障碍的用药经验。收集丁元庆教授治疗抽动障碍的病案,采用关联规则Apriori算法、复杂系统熵聚类等无监督数据挖掘方法,对筛选出的800首处方进行分析,确定处方中药物的使用频次,药物之间的关联规则,挖掘出12个核心组合和6首新处方,用药以调肝熄风,凉血止痉,清心安神为主,随证化裁,应用灵活,配伍严谨。     

基于数据挖掘的中医治疗阳痿用药规律分析

目的:探讨中医治疗阳痿病的用药规律。方法:收集古籍以及全国名老中医药专家治疗阳痿病处方,基于中医传承辅助系统软件构建数据库,采用关联规则Apriori算法和复杂系统熵聚类方法,确定处方中各药物和药物组合的使用频数及药物之间的关联规则等。结果:高频药物包括菟丝子、熟地黄、当归、枸杞子、淫羊藿等;高频药物组合包括"枸杞子、菟丝子","肉苁蓉、菟丝子","枸杞子、淫羊藿"等;置信度为0.6以上的关联规则包括"茯苓-菟丝子","熟地黄-枸杞子","柴胡-当归"等。结论:中医治疗阳痿多用温补肾阳、益气养血之品。     

基于关联规则和复杂系统熵聚类的糖尿病用药规律研究

目的:基于中医传承辅助平台(TCMISS)探讨糖尿病的中药处方用药规律。方法:从文献中收集近10余年治疗糖尿病的中药处方,采用关联规则Apriori算法,进行基于改进的互信息法的药物间关联度分析;并以关联度分析结果为基础,依据相关度与惩罚度约束,进行基于复杂系统熵聚类的药物核心组合分析;用无监督熵层次聚类算法,获得治疗糖尿病新处方;根据结果绘制出用药关联规则网络图、新方的核心组合药物网络图。上述操作基于TCMISS V1.1完成。结果:对筛选出的110个处方进行分析,明确了处方中药物的使用频次规律,药物之间的关联规则,挖掘出16个核心组合和8首新处方。结论:基于关联规则和聚类分析的数据挖掘手段,适合中医方剂用药规律的挖掘、分析和总结。以补益气阴为主并灵活配伍清热药、活血化瘀药,同时根据不同证型考究药物的配伍组合对提高糖尿病的疗效有重要意义。