IgA肾病数据管理与辅助诊断分析

发布时间：2019-05-24 20:12

【摘要】：医院信息系统(HIS)正在向着自动化与智能化的方向不断发展,肾内科的信息化建设也是其重要的组成部分。推进肾内科的信息化建设也将为肾脏疾病临床数据的管理与挖掘提供帮助,为肾病的诊断和治疗提供一定的依据。IgA肾病,以肾小球系膜区沉积为主的一组病理诊断疾病。自1986年报导以来已被认为是世界上最为常见的一种原发性肾小球疾病,在亚太地区发病率明显较高,是引起终末期肾衰竭的重要原因之一。为了更有效的防治IgA肾病,进行更深入的研究也变得尤为重要。研究需要搜集大量的临床信息,因此利用现代信息技术进行处理无疑提供了有效的途径,根据云南省第一人民医院肾内科的需求,设计与实现了一套规范、高效、易于扩展的肾病数据库管理系统。在此基础上,对肾病数据进行挖掘分析并将结果尝试应用于临床辅助诊断。本文将探讨IgA肾病临床资料的信息化管理和应用以及对临床指标的挖掘研究。根据需求分析设计肾病临床数据库的构架和功能,利用JAVA语言和ORACLE数据库,设计并建立了肾病临床数据库系统。可以将大量宝贵的患者临床资料进行保存;可以方便的进行数据库中信息的修改和更新;并提供快速、简便的查阅信息功能,从中得到相关的临床信息。对于医药、治疗情况、随访信息等部分以及用户、模块、岗位的管理也进行了更自动化的设计实现。该数据库系统也是基于多中心和多单位的,以云南省第一人民医院为中心,可以联合其他州市的肾病临床数据进行大数据的研究。本文研究课题是以IgA肾病临床检测指标研究的数据为基础,并以此为平台,利用一种基于最优风险与预防模型算法进行数据挖掘。所提出的方法将依据患者检测出的部分实验室检查指标进行挖掘,得出患病时检查指标的高风险范围。实验结果表明:该方法可以检测出患者患病时的指标数值的风险范围,为疾病预测提供帮助。另外,利用上述的挖掘方法与结果,与现代计算机技术相结合,实现一种IgA肾病的辅助诊断系统。医务人员可以对就医患者的检测指标进行初步的辅助诊断。该系统操作简单,也能在一定程度上满足患者的自我辅助诊断需求。
[Abstract]:Hospital information system (HIS) is developing towards the direction of automation and intelligence, and the information construction of kidney department is also an important part of it. Promoting the information construction of renal medicine will also provide help for the management and mining of clinical data of renal diseases and provide a certain basis for the diagnosis and treatment of kidney disease. IGA nephropathy is a group of pathological diagnosis diseases dominated by Mesangial deposition. Since 1986, it has been considered to be one of the most common primary glomerular diseases in the world. It has a significantly higher incidence in the Asia-Pacific region and is one of the important causes of end-stage renal failure. In order to prevent and treat IgA kidney disease more effectively, it is particularly important to carry out more in-depth research. The research needs to collect a lot of clinical information, so the use of modern information technology to deal with it undoubtedly provides an effective way to design and implement a set of norms and high efficiency according to the needs of the Department of Nephrology of the first people's Hospital of Yunnan Province. Easy to expand kidney disease database management system. On this basis, the data of kidney disease were excavated and analyzed and the results were tried to be applied to clinical auxiliary diagnosis. This paper will explore the information management and application of clinical data of IgA nephropathy and the mining of clinical indexes. According to the demand analysis, the structure and function of renal disease clinical database were designed. Using Java language and ORACLE database, the kidney disease clinical database system was designed and established. A large number of valuable clinical data of patients can be saved, the information in the database can be modified and updated conveniently, and the related clinical information can be obtained by providing rapid and simple access to information. For medicine, treatment, follow-up information and other parts, as well as users, modules, post management is also more automated design and implementation. The database system is also based on multi-center and multi-unit, taking the first people's Hospital of Yunnan Province as the center, which can combine the clinical data of kidney disease in other cities to carry out big data's research. In this paper, based on the data of clinical detection index of IgA nephropathy, a data mining algorithm based on optimal risk and prevention model is used as a platform. The proposed method will be excavated according to some laboratory examination indexes detected by the patients, and the high risk range of the examination indexes at the time of illness will be obtained. The experimental results show that this method can detect the risk range of the index value when the patient is ill, and provide help for disease prediction. In addition, using the above mining methods and results, combined with modern computer technology, a kind of auxiliary diagnosis system of IgA nephropathy is realized. Medical staff can make a preliminary auxiliary diagnosis of the detection indexes of patients seeking medical treatment. The system is simple to operate and can meet the needs of self-aided diagnosis to a certain extent.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：R197.324;TP311.13

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