【摘要】：隨著醫(yī)院信息化建設的推進,各醫(yī)院都積累了大量的臨床文檔,已成為醫(yī)療大數(shù)據(jù)的重要組成部分。對臨床文檔的分析和挖掘,在疾病診斷、治療以及病情預測上具有實際意義。由于臨床文檔本質上是一種非結構化文本數(shù)據(jù),在分析與挖掘之前,往往需要通過臨床文檔結構化處理系統(tǒng)抽取出其中的結構化信息,形成可供數(shù)據(jù)分析工具和機器學習算法使用的規(guī)范化數(shù)據(jù)。眾多醫(yī)院在為患者提供醫(yī)療服務的同時積累了大量的臨床文檔,如何為這些醫(yī)院提供高效的臨床文檔結構化服務是急需解決的問題。本課題的前期工作已對集中式臨床文檔結構化處理進行了研究,也提出了單機版本的臨床文檔結構化處理算法,構建了集中式的臨床文檔結構化系統(tǒng)。但是,以單機的方式為眾多醫(yī)院提供海量臨床文檔結構化處理服務,不管在處理速度還是存儲容量方面都無法滿足用戶的需求。因此,本文在前期工作的基礎上,構建了基于云服務的分布式臨床文檔結構化系統(tǒng),解決了目前臨床文檔結構化處理過程中存在的處理速度慢,存儲容量小以及數(shù)據(jù)難共享的問題。該系統(tǒng)為不同醫(yī)院提供分布式臨床文檔存儲服務和臨床文檔分布式結構化處理服務。具體而言,該系統(tǒng)采用了Hadoop分布式架構和OpenStack云計算管理平臺,其中Hadoop架構提供了分布式臨床文檔存儲服務和結構化處理服務,OpenStack提供了計算資源的合理分配以及臨床文檔的共享服務。本文的主要工作包括:(1)介紹了非結構化臨床文檔,闡述了超聲類型臨床文檔的組成結構,并給出了超聲文檔結構化處理思路。在此基礎上,提出了基于云服務的臨床文檔結構化系統(tǒng)整體框架。該系統(tǒng)由五個模塊組成,分別為云資源管理模塊、非結構化臨床文檔上傳模塊、臨床文檔存儲及管理模塊、臨床文檔結構化模塊和結構化數(shù)據(jù)存儲及管理模塊,本文分別闡述了以上五個模塊的設計思想和實現(xiàn)流程。(2)詳細闡述了臨床文檔結構化模塊的設計與實現(xiàn)過程。該過程主要由兩個階段組成,第一階段對不同樣本的臨床文檔進行指標模板的提取,第二階段實現(xiàn)基于MapReduce的臨床文檔分布式結構化處理。其中,Map階段包括對數(shù)據(jù)的預處理、短句切分、指標模板套用和Key,Value值的確定四個步驟,實現(xiàn)了對每條臨床文檔數(shù)據(jù)的結構化處理。Reduce階段對分布式結構化處理后的數(shù)據(jù)按照Key值進行匯總。(3)闡述了基于云服務的臨床文檔結構化系統(tǒng)的部署與實現(xiàn)。給出了OpenStack結合Hadoop的具體部署過程,闡述了本系統(tǒng)中各個模塊的具體實現(xiàn)過程。接著,展示了供用戶操作的Web界面及其實現(xiàn)方式,最后,對本系統(tǒng)的運行效果進行評估。
[Abstract]:With the advance of hospital information construction, various hospitals have accumulated a large number of clinical documents, which has become an important part of medical big data. The analysis and mining of clinical documents are of practical significance in the diagnosis, treatment and prediction of the disease. Because the clinical document is essentially a kind of unstructured text data, before analyzing and mining, it is often necessary to extract the structured information from the structured processing system of the clinical document. Form standardized data that can be used by data analysis tools and machine learning algorithms. Many hospitals have accumulated a large number of clinical documents while providing medical services to patients. How to provide efficient structured services for clinical documents in these hospitals is an urgent problem to be solved. The previous work of this paper has carried on the research to the centralized clinical document structured processing, also has proposed the single machine version clinical document structured processing algorithm, has constructed the centralized clinical document structured system. However, a large amount of structured processing services for clinical documents are provided to many hospitals in a stand-alone manner, which can not meet the needs of users in terms of processing speed or storage capacity. Therefore, on the basis of the previous work, this paper constructs a distributed clinical document structured system based on cloud services, which solves the slow processing speed existing in the structured processing of clinical documents at present. Small storage capacity and data sharing problems. The system provides distributed clinical document storage service and clinical document distributed structured processing service for different hospitals. Specifically, the system adopts Hadoop distributed architecture and OpenStack cloud computing management platform, in which Hadoop architecture provides distributed clinical document storage services and structured processing services. OpenStack provides reasonable allocation of computing resources and sharing of clinical documents. The main work of this paper is as follows: (1) the unstructured clinical documents are introduced, the composition and structure of ultrasonic clinical documents are expounded, and the idea of structural processing of ultrasonic documents is given. On this basis, the whole framework of clinical document structured system based on cloud service is proposed. The system consists of five modules: cloud resource management module, unstructured clinical document uploading module, clinical document storage and management module, clinical document structured module and structured data storage and management module. In this paper, the design idea and implementation flow of the above five modules are described respectively. (2) the design and implementation process of the structured module of clinical documents is described in detail. The process mainly consists of two phases. In the first stage, the index templates are extracted from the clinical documents of different samples, and the distributed structured processing of clinical documents based on MapReduce is implemented in the second stage. Among them, the Map stage includes four steps: data preprocessing, short sentence segmentation, indicator template application and Key, value determination, which includes four steps: data pre-processing, short sentence segmentation, indicator template application and Key, value determination. In the reduce stage, the distributed structured data are summarized according to the key values. (3) the deployment and implementation of a structured clinical document system based on cloud services is described. The concrete deployment process of OpenStack combined with Hadoop is given, and the realization process of each module in the system is described. Then, the Web interface for user operation and its implementation are shown. Finally, the operating effect of the system is evaluated.
【學位授予單位】：東華大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP311.52;TP393.09

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