数据挖掘技术在医学中的应用

由于医学信息发展产生了大量纷繁复杂的临床数据,需要引进一门新的技术--数据挖掘和知识发现技术,用数据挖掘方法抽取数据中的趋势及规律性.可以辅助医务人员快速准确地诊断、预测、监控和确定最优的治疗方案.目前,数据挖掘已经运用在很多医学应用领域中.     

基于数据挖掘的老年痴呆与老年失眠用药规律及关联

目的 通过数据挖掘技术分析老年痴呆与老年失眠的中医用药规律,探寻两种疾病“同治”的客观依据。方法 采用SPSS22.0软件进行描述性统计和系统聚类分析,采用SPSS Clementine12.0软件进行关联性分析,选择Apriori算法建立数据挖掘模型。结果 老年痴呆和老年失眠的高频药物可分别聚为6类;关联分析得到的老年痴呆核心药对为石菖蒲-远志,其他药物按功能主治可大致分为滋阴补肾、健脾益气、化痰、活血、安神。老年失眠的核心药对为酸枣仁-远志、茯苓-白术、龙骨-牡蛎,纳入的关联药物多与安神药配伍使用。结论 老年痴呆与老年失眠存在共同的治法和常用药对,即补肾健脾(熟地-山药)、宁心安神(酸枣仁-夜交藤)、活血化痰(石菖蒲-郁金、远志-当归-石菖蒲)。     

基于深度学习的医学图像分割方法

近年来,日渐成熟的人工智能深度学习技术使得众多领域逐渐实现自动化智能化作业。在医疗领域,随着医疗数据电子化和互联网医疗的发展,基于卷积神经网络实现包含定位、分割和分类于一体的辅助诊断系统应用已成为新型医疗模式发展的必然趋势。医学影像分割技术是医疗图像自动分析中的难点和重点,目前仍面临许多亟待解决的问题。该文将从临床医学影像的特点、深度学习主流分割网络和医学图像分割网络在临床中的应用3个方面对医学图像分割领域的研究进展进行系统综述,并进一步分析卷积神经网络在医学影像分割任务中的发展现状、面临的挑战以及未来的发展方向。     

探究医学超声图像分割技术以及发展方向

图像分割技术在医学超声图像的定性、定量分析中占据十分重要的地位,它对后续的分析、处理工作有直接的影响。但是,尽管目前有大量的文献记载了关于图像的分割方法,对于许多具有复杂特性的医学超声图像,往往这些方法就起不到多少作用了。本文主要以医学的超声图像特性的分析为基础,分别对医学超声图像的分割方法进行介绍及评价,并对其发展的方向、趋势进行了简单的探讨。     

基于数据挖掘分析邵冬珊主任治疗慢性乙型肝炎用药规律

目的:运用数据挖掘技术分析邵冬珊主任治疗慢性乙型病毒性肝炎的用药规律。方法:收集邵冬珊治疗慢性乙型肝炎门诊处方数据,运用Microsoft Excel、SPSS Modeler 18.0及Cytoscape 3.9.1软件,统计处方中的药物使用频次、性味归经及药物之间的关联规则,提取核心药对,分析用药规律。结果:筛选出处方共679张,涉及中药204味,高频用药包含甘草、丹参、败酱草、白术等;药性主要为温性;药味主要为甘味、苦味;归经主要为肝经。关联规则分析显示,枸杞子、半夏-黄芩等为治疗慢性乙型肝炎核心药对。结论:邵冬珊在治疗慢性乙型肝炎方面以扶正气、和枢机、解郁结为主,并根据患者不同证候随证加减。     

精准医学:全基因组关联研究在药物基因组学中的进展

<正>现代医学一直遵循精准理念,不断融入新理论、新技术、新设备以提高临床实践的准确性和客观性[1],比如CT、磁共振成像、染色体诊断等技术。精准理念克服传统医疗的盲目性,减少漏诊和误诊,避免治疗不足或过度,是现代医学进步的推动力。在世界范围内,精准医学被研究者广泛接受[1,2]。精准用药是精准医学的重要分支;在美国,三分之一的处方药被认为无效,每年浪费约7 126亿元人民币(1 000亿美元);对患者健康不仅无益,反而具有潜在危险性[3]。药     

基于数据挖掘对急性缺血性脑卒中中医用药规律的分析

目的分析急性缺血性脑卒中的中医用药规律。方法收集2000年1月至2016年5月中医药治疗急性缺血性脑卒中的处方,应用SPSS Clementine12.0关联规则等数据挖掘方法,得到药物频次、药物组合、关联规则等,分析治疗急性缺血性脑卒中的用药规律。结果运用SPSS Clementine12.0对筛选出的79首处方进行分析,得到治疗急性缺血性脑卒中的高频词药物为川芎、大黄、天麻、地龙、丹参、赤芍、甘草、石菖蒲、胆南星、钩藤、半夏等26味药物;同时在S≥14%,C≥82%,L≥1.0条件下挖掘出27个关联规则,并聚类分析出5个结果。结论急性缺血性脑卒中气虚血瘀、痰热腑实、风痰阻络最为常见,而补气活血、祛瘀通络、清热化痰药在治疗上疗效明显,应用广泛。     

特发性间质性肺炎新分类:从专家共识到循证医学

特发性肺纤维化 (ＩＰＦ)是一病因未明的慢性进行性致纤维化肺疾病。长期以来在命名、病理学分类、临床病程、疗效反应、预后评估、临床和组织病理学诊断诸多方面 ,一直存在有待界定、重新认识或需共识的一些问题[1,2 ] 。产生这些问题的根本原因是由于特发性间质性肺炎 (ＩＩＰ) ,其中包括ＩＰＦ,代表着一组病因未明的异质性疾病 ,它们的临床表现非常相似 ,但缺乏特异性 ,不能依据临床资料做出确切诊断。且间质性肺炎的分类是以组织病理学为基础 ,根据其各自不同特点划分类型的[1,3 ] 。不同的组织类型 ,如普通型间质性肺炎 (ＵＩＰ)、特发…     

基于数据挖掘关幼波教授辨治肝病的证治规律

目的:基于异病同治的中医治则,挖掘关幼波教授在肝病诊治中的辨证及遣方用药特点,探索关幼波教授辨治肝病的证治规律。方法:收集关幼波教授治疗肝病的医案,运用古今医案云平台(V2.2.3)软件进行统计描述及关联分析等,总结关幼波教授辨治肝病的常见证候及相应治法、用药等规律。结果:关幼波教授辨治肝病的病位主要在肝、脾、胆、肾,病性以虚、湿、热、瘀为主;常见中医证候有肝胆湿热证、气虚血滞证、气血两虚证、肝郁血滞证、阴虚血热证、肝肾阴虚证等;治法有清热利湿、活血化痰、补气养血、活血解毒、舒肝解毒、滋补肝肾等;关联分析所得常用药对8对、中医证候-中药组合10类。结论:关幼波教授辨治肝病重视正邪关系,多从湿、热、瘀、虚着手,辨证时主张十纲辨证、正邪兼顾,治疗上重视调理气血、中州当先、活血化痰等。     

基于数据挖掘的中药专利复方治疗慢性萎缩性胃炎的用药规律分析

[目的]基于数据挖掘方法分析中药专利复方治疗慢性萎缩性胃炎的用药及配伍规律。[方法]使用中国知网专利数据库检索治疗慢性萎缩性胃炎的中药专利复方,建立Excel数据表对数据进行筛选处理,应用数据挖掘软件进行频次统计、关联分析、聚类分析和复杂网络分析。[结果]筛选治疗慢性萎缩性胃炎的中药专利复方296个,药物四气以温、平为主,五味以甘、苦为主,归经以脾、胃经为主。频次较高的前10位中药分别为甘草、白术、白芍、黄芪、党参、茯苓、陈皮、木香、半夏、丹参;频繁项集显示药物组合以益气健脾、理气和胃为主;关联规则分析显示常见药对包括白芍-甘草、白术-甘草、白术-茯苓、白术-党参、丹参-白术、延胡索-白芍、莪术-黄芪、香附-白芍等;聚类分析得到6类药物;核心药物网络由35味中药组成。[结论]数据挖掘研究为慢性萎缩性胃炎的临床治疗提供了参考;治疗慢性萎缩性胃炎应遵循扶正祛邪的基本治则,以益气健脾为基本治法,兼顾理气活血、化湿燥湿、清热解毒、益胃养阴等方法。     

Identifying combinatorial biomarkers by association rule mining in the CAMD Alzheimer's database

The concept of combinatorial biomarkers was conceived when it was noticed that simple biomarkers are often inadequate for recognizing and characterizing complex diseases. Here we present an algorithmic search method for complex biomarkers which may predict or indicate Alzheimer's disease (AD) and other kinds of dementia. We show that our method is universal since it can describe any Boolean function for biomarker discovery. We applied data mining techniques that are capable to uncover implication-like logical schemes with detailed quality scoring. The new SCARF program was applied for the Tucson, Arizona based Critical Path Institute's CAMD database, containing laboratory and cognitive test data for 5821 patients from the placebo arm of clinical trials of large pharmaceutical companies, and consequently, the data is much more reliable than numerous other databases for dementia. The results of our study on this larger than 5800-patient cohort suggest beneficial effects of high B12 vitamin level, negative effects of high sodium levels or high AST (aspartate aminotransferase) liver enzyme levels to cognition. As an example for a more complex and quite surprising rule: Low or normal blood glucose level with either low cholesterol or high serum sodium would also increase the probability of bad cognition with a 3.7 multiplier. The source code of the new SCARF program is publicly available at http://pitgroup.org/static/scarf.zip.     

基于数据挖掘的动脉粥样硬化易损斑块动物模型分析

[目的]统计动脉粥样硬化易损斑块(VP)动物模型造模方法及应用情况。[方法]检索2016年10月—2021年10月发表在中国知网、Pubmed、万方数据库关于VP动物造模的相关文献,对文献中的造模动物、造模方法、造模周期以及模型评价方法、相应检测指标等进行统计分析。[结果]实验动物使用最多的,依次为6～12周载脂蛋白E基因缺陷小鼠,12～16周新西兰大白兔以及34周家族性高胆固醇血症猪。造模方法依次为高脂高胆固醇饮食诱导、动脉结扎,或结合主动脉内皮球囊拉伤、化学触发、免疫诱导等。造模周期为8周到1年不等,以12～18周的为最多。评价方法多为病理染色,并结合酶联免疫吸附法、Western blot、实时荧光定量PCR、流式细胞仪检测等手段;彩色多普勒超声、心脏灌注显影及体内活细胞示踪技术用于VP的活体探测。[结论]高脂高胆固醇饮食饲养,或结合手术损伤建立VP模型具有很好的可重复性。若能研发高性价比的活体探测方法,将极大提高动脉粥样硬化疾病的研究效率。     

Oral administration of East Asian herbal medicine for peripheral neuropathy: A protocol for systematic review and meta-analysis with using association rule analysis to identify core herb pattern

Background:Peripheral neuropathy (PN) is one of the most common medical problems encountered. Since the pathophysiology and symptom manifestation characteristics of PN are very diverse, it is difficult to provide an appropriate treatment. East Asian herbal medicine (EAHM) has long contributed to the treatment of neurological and pain disorders. The goal of this systematic review is to measure the efficacy and safety of EAHM for PN and to identify core herb patterns. In order to derive a more conservative result, a random effect model will be applied regardless of the significance of heterogeneity.Methods:We will search 10 databases to identify suitable studies. There will be no restrictions regarding language or publication date. Primary outcomes will be nerve conduction velocity and response rate. Secondary outcomes will be any objective tool that can measure the efficacy of EAHM, and adverse events will be included. We will perform a meta-analysis of trials with the same intervention and outcome with comparator in a similar population. Meanwhile, in order to explore significant potential correlation in herb preparation, association rule analysis based on the Apriori algorithm will be performed on the collected composition data of herbal medicines.Results:This study will provide scientific evidence for the treatment of EAHM for PN.Conclusions:Based on the results of this review, it is expected that the efficacy and safety of EAHM for PN can be confirmed. In addition, through additional analysis using data mining techniques, it will be possible to present a core herb pattern related to this research topic.     

基于数据挖掘分析中医治疗老年肛周会阴部坏死性筋膜炎术后用药规律

目的 基于数据挖掘分析中医治疗老年肛周会阴部坏死性筋膜炎术后的用药规律,指导临床用药.方法 检索中文文献库,纳入相关文献.根据分层聚类、关联规则的数据挖掘方法,对高频用药及组方规律进行分析.结果 纳入文献中,有31篇涉及口服方剂,24篇涉及外洗方剂,总共涉及处方107份.高频口服药19味,药对18对,聚类方4则;高频外...     

基于CT分型方法的儿童肺结核临床特征分析

目的 分析儿童肺结核CT特征的临床特点。方法 回顾性分析首都医科大学附属北京儿童医院2006年7月至2014年12月经临床诊断并确诊为肺结核的734例患儿的临床资料(包括年龄、性别、临床表现,疫苗接种史、接触史及实验室检查等),基于CT分型对其CT特征、临床特点进行分析。结果 734例患儿中159例(21.7%)为经病原学检测确诊;CT分型中原发性肺结核和气管、支气管结核最多见(365例,50.4%),并发2种及以上类型者次之(199例,27.3%);3岁以下婴幼儿以原发性肺结核和气管、支气管结核多见(189例,26.1%), 7~14岁青春期儿童以结核性胸膜炎多见(94例,13.0%);并发肺外结核患者以结核性脑膜炎(109例,34.5%)及肺外播散累及2个及以上器官或组织者(103例,32.6%)最多见。192例(26.2%)患儿并发其他疾病或患有基础疾病。结论 不同年龄阶段患儿的肺结核CT分型不同,且常并发肺外结核;儿童肺结核CT表现有其自身特点及年龄分布特点。     

Data mining and analysis of scientific research data records on Covid-19 mortality,immunity, and vaccine development - In the first wave of the Covid-19 pandemic

Background and aimsCovid-19 is a global pandemic that requires a global and integrated response of all national medical and healthcare systems. Covid-19 exposed the need for timely response and data sharing on fast spreading global pandemics. In this study, we investigate the scientific research response from the early stages of the pandemic, and we review key findings on how the early warning systems developed in previous epidemics responded to contain the virus.MethodsWe conducted data mining of scientific literature records from the Web of Science Core Collection, using the topics Covid-19, mortality, immunity, and vaccine. The individual records are analysed in isolation, and the analysis is compared with records on all Covid-19 research topics combined. The data records are analysed with commutable statistical methods, including R Studio’s Bibliometrix package, and the Web of Science data mining tool.ResultsFrom historical analysis of scientific data records on viruses, pandemics and mortality, we identified that Chinese universities have not been leading on these topics historically. However, during the early stages of the Covid-19 pandemic, the Chinese universities are strongly dominating the research on these topics. Despite the current political and trade disputes, we found strong collaboration in Covid-19 research between the US and China. From the analysis on Covid-19 and immunity, we wanted to identify the relationship between different risk factors discussed in the news media. We identified a few clusters, containing references to exercise, inflammation, smoking, obesity and many additional factors. From the analysis on Covid-19 and vaccine, we discovered that although the USA is leading in volume of scientific research on Covid-19 vaccine, the leading 3 research institutions (Fudan, Melbourne, Oxford) are not based in the USA. Hence, it is difficult to predict which country would be first to produce a Covid-19 vaccine.ConclusionsWe analysed the conceptual structure maps with factorial analysis and multiple correspondence analysis (MCA), and identified multiple relationships between keywords, synonyms and concepts, related to Covid-19 mortality, immunity, and vaccine development. We present integrated and corelated knowledge from 276 records on Covid-19 and mortality, 71 records on Covid-19 and immunity, and 189 records on Covid-19 vaccine.     

Identification of novel risk genes associated with type 1 diabetes mellitus using a genome‐wide gene‐based association analysis

Aims/Introduction

Type 1 diabetes mellitus is a serious disorder characterized by destruction of pancreatic β-cells, culminating in absolute insulin deficiency. Genetic factors contribute to the susceptibility of type 1 diabetes mellitus. The aim of the present study was to identify more susceptibility genes of type 1 diabetes mellitus.

Materials and Methods

We carried out an initial gene-based genome-wide association study in a total of 4,075 type 1 diabetes mellitus cases and 2,604 controls by using the Gene-based Association Test using Extended Simes procedure. Furthermore, we carried out replication studies, differential expression analysis and functional annotation clustering analysis to support the significance of the identified susceptibility genes.

Results

We identified 452 genes associated with type 1 diabetes mellitus, even after adapting the genome-wide threshold for significance (P < 9.05E-04). Among these genes, 171 were newly identified for type 1 diabetes mellitus, which were ignored in single-nucleotide polymorphism-based association analysis and were not previously reported. We found that 53 genes have supportive evidence from replication studies and/or differential expression studies. In particular, seven genes including four non-human leukocyte antigen (HLA) genes (RASIP1, STRN4, BCAR1 and MYL2) are replicated in at least one independent population and also differentially expressed in peripheral blood mononuclear cells or monocytes. Furthermore, the associated genes tend to enrich in immune-related pathways or Gene Ontology project terms.

Conclusions

The present results suggest the high power of gene-based association analysis in detecting disease-susceptibility genes. Our findings provide more insights into the genetic basis of type 1 diabetes mellitus.