本文選題：心肺性職業(yè)病 + Apriori算法計(jì)算模型��； 參考：《青島科技大學(xué)》2017年碩士論文

【摘要】：本課題是基于Hadoop平臺(tái)的分布式醫(yī)療大數(shù)據(jù)挖掘算法和模型的研究,選取目前深受人們重視的心肺性職業(yè)病大數(shù)據(jù),提取醫(yī)院職業(yè)病科電子病歷系統(tǒng)中的非結(jié)構(gòu)化數(shù)據(jù)進(jìn)行挖掘分析。本研究主要對(duì)該疾病進(jìn)行模式分析,通過(guò)分析病患的標(biāo)志性物及相關(guān)輔助指標(biāo),研究病例的各檢驗(yàn)項(xiàng)之間,以及各檢驗(yàn)項(xiàng)與疾病之間的客觀(guān)規(guī)律,從而得出患者發(fā)病的影響因素,實(shí)現(xiàn)提前預(yù)防;之后還對(duì)心肺性職業(yè)病患者的一般性并發(fā)癥進(jìn)行了研究,以能夠得到心肺病與不同病癥之間的并發(fā)關(guān)系,能對(duì)相關(guān)病癥的患者給予提醒,實(shí)現(xiàn)提前就醫(yī)、精準(zhǔn)治療。主要內(nèi)容如下:(1)收集臨床電子病歷系統(tǒng)中心肺性職業(yè)病患者的病歷數(shù)據(jù),對(duì)非結(jié)構(gòu)化的文本醫(yī)療數(shù)據(jù)進(jìn)行預(yù)處理,建立醫(yī)療文本數(shù)據(jù)的結(jié)構(gòu)化模型,并為了保證研究結(jié)果的精準(zhǔn)對(duì)結(jié)構(gòu)化文本數(shù)據(jù)進(jìn)一步進(jìn)行結(jié)構(gòu)類(lèi)型的轉(zhuǎn)換處理;(2)綜合分析不同數(shù)據(jù)挖掘算法,根據(jù)心肺性職業(yè)病數(shù)據(jù)挖掘的不同目的,選取經(jīng)典的關(guān)聯(lián)規(guī)則Apriori算法并進(jìn)行改進(jìn),加入興趣度的限制,建立最優(yōu)數(shù)據(jù)分析挖掘模型;(3)根據(jù)心肺性職業(yè)病體征與病歷中的檢驗(yàn)項(xiàng)、病人個(gè)人信息等醫(yī)療大數(shù)據(jù)信息,以臨床信息為對(duì)象,從數(shù)據(jù)挖掘技術(shù)應(yīng)用入手,研究心肺性職業(yè)病與各項(xiàng)指標(biāo)的關(guān)系,分析疾病生理指標(biāo)的分布特點(diǎn),揭示指標(biāo)與疾病之間、疾病與職業(yè)間存在的特定關(guān)系;(4)根據(jù)模型對(duì)心肺性職業(yè)病檢驗(yàn)項(xiàng)的分布模式挖掘,通過(guò)對(duì)不同患者并發(fā)癥的研究,挖掘出本病癥與各個(gè)并發(fā)癥的關(guān)系,依據(jù)病人具體情況定制個(gè)性化的治療方案,實(shí)現(xiàn)對(duì)病患的精準(zhǔn)治療;(5)搭建Hadoop平臺(tái)環(huán)境,將集中存儲(chǔ)的數(shù)據(jù)信息導(dǎo)入分布式存儲(chǔ)平臺(tái)Hadoop中,實(shí)現(xiàn)基于Hadoop平臺(tái)的數(shù)據(jù)挖掘和處理。
[Abstract]:This topic is based on the Hadoop platform of distributed medical large data mining algorithms and models, select the major data of cardiopulmonary occupational diseases which are being paid much attention to, and extract unstructured data in the electronic medical record system of the hospital occupational medical records. This study mainly analyzes the disease mode and analyzes the disease. The markers and related auxiliary indexes of the cases were studied, and the objective laws between the examination items and the disease were studied, and the influencing factors of the patients were obtained, and the early prevention was achieved. Then the general complications of the patients with cardiopulmonary disease were studied in order to be able to get between the heart and the different diseases. The main contents are as follows: (1) collect the medical records of the patients with pulmonary occupational disease in the center of the clinical electronic medical record system, preprocess the unstructured text medical data, build a structured model of medical text data, and guarantee the research. The result is accurate to structural type text data conversion processing; (2) comprehensive analysis of different data mining algorithms, according to the different purposes of the heart and lung occupational disease data mining, select the classical association rules Apriori algorithm and improve, join the limit of interest, establish the optimal data analysis mining model; (3) root According to the examination items of cardiopulmonary occupational diseases and medical records, the information of patients' personal information and other medical data, the relationship between cardiopulmonary occupational diseases and various indexes is studied from the application of data mining technology, and the distribution characteristics of disease physiological indexes are analyzed, and the existence of indicators and diseases and between diseases and professions is revealed. Specific relationship; (4) excavate the distribution pattern of cardiopulmonary occupational disease inspection items according to the model, through the study of the complications of different patients, excavate the relationship between the disease and the various complications, customize the individualized treatment scheme according to the specific situation of the patient, realize the precise treatment of the patients, and (5) build the Hadoop platform environment, and will concentrate the storage Data information is imported into the distributed storage platform Hadoop to realize data mining and processing based on Hadoop platform.

【學(xué)位授予單位】：青島科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：R135;TP311.13

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