本文選題：數(shù)據(jù)庫 + 數(shù)據(jù)挖掘　； 參考：《皖南醫(yī)學(xué)院》2014年碩士論文

【摘要】：目的：以糖尿病患者作為研究對象，，采用先進的數(shù)據(jù)庫開發(fā)平臺，獲取糖尿病患者臨床信息、基本信息并通過采集超聲心動圖原始構(gòu)型及功能數(shù)據(jù)信息建立數(shù)據(jù)庫，根據(jù)數(shù)據(jù)挖掘（Data Mining，DM）原理，利用數(shù)據(jù)挖掘工具對大樣本的糖尿病患者的臨床相關(guān)數(shù)據(jù)及心臟功能的有關(guān)超聲數(shù)據(jù)進行數(shù)據(jù)挖掘，得到影響糖尿病心臟功能（左室舒張功能）變化的關(guān)鍵影響因素及特征性指標(biāo)，并揭示出各影響因素與心臟功能改變之間的潛在的、有價值的規(guī)律，分析各指標(biāo)之間地變化規(guī)律，了解糖尿病心臟功能的動態(tài)變化，并通過數(shù)據(jù)模型的建立對糖尿病心臟功能的變化進行預(yù)測并對糖尿病心臟并發(fā)癥的早期干預(yù)、動態(tài)監(jiān)測、臨床治療、療效觀察等提供可行性的決策支持。 方法：選擇2012年7月至2014年2月來我院進行超聲心動圖檢查檢查并已臨床確診為糖尿病的360例患者，采用高檔彩色多普勒超聲診斷儀按照統(tǒng)一規(guī)范化檢查、測量進行操作，獲取糖尿病患者心臟構(gòu)型、功能超聲數(shù)據(jù)，并且記錄受檢者身高、體重、腹圍、體表面積等形體指標(biāo)，通過與醫(yī)院信息系統(tǒng)（hospital informationsystem，HIS）連接查詢獲取糖尿病患者臨床信息及基本信息（患者有無糖尿病家族史、血糖、血脂、血壓、是否高糖、高熱量飲食、是否高蛋白飲食、是否抽煙、是否飲酒、以及心電圖的改變等相關(guān)數(shù)據(jù)），用以上數(shù)據(jù)源建立糖尿病心臟功能數(shù)據(jù)庫，以SQL Server2008作為數(shù)據(jù)庫管理工具，利用SQL Server2008數(shù)據(jù)挖掘工具對糖尿病患者的基本信息、臨床信息及反映心臟功能的超聲數(shù)據(jù)進行數(shù)據(jù)挖掘，挖掘出各影響因素與糖尿病心臟功能（左室舒張功能）改變的潛在的、有價值的規(guī)律，分析各指標(biāo)之間地變化規(guī)律，了解糖尿病心臟功能（左室舒張功能）的動態(tài)變化，初步設(shè)計了糖尿病患者心臟功能（左室舒張功能）改變的簡單模型。 結(jié)果：建立包含糖尿病患者的基本信息、臨床信息及心臟構(gòu)型、功能數(shù)據(jù)的關(guān)系數(shù)據(jù)庫，并對關(guān)系數(shù)據(jù)庫進行預(yù)處理轉(zhuǎn)換成適合數(shù)據(jù)挖掘的事務(wù)數(shù)據(jù)庫，進行數(shù)據(jù)挖掘初步設(shè)計了糖尿病患者心臟功能（左室舒張功能）改變的初步模型。通過功能數(shù)據(jù)模型的建立對糖尿病心臟功能的變化進行預(yù)測并對糖尿病心臟并發(fā)癥的早期干預(yù)、動態(tài)監(jiān)測、臨床治療、療效觀察等提供可行性的決策支持。提供了一種對糖尿病心臟功能變化的影響因素、相關(guān)的功能指標(biāo)進行分析的方法，通過數(shù)據(jù)挖掘我們可以得到糖尿病心臟功能改變與糖尿病遺傳史、血糖、血壓、血脂、BMI及腹圍、左房容積指數(shù)等密切相關(guān)，可以初步建立反映糖尿病患者左室舒張功能變化的數(shù)據(jù)模型。 結(jié)論：利用數(shù)據(jù)挖掘技術(shù)可以有效地對大量的醫(yī)學(xué)信息進行挖掘，可以從中提取有價值的規(guī)則并獲取知識，可以及時準(zhǔn)確地對心臟功能改變進行預(yù)測，對糖尿病心臟并發(fā)癥的早期干預(yù)、動態(tài)監(jiān)測、臨床治療、療效觀察等提供可行性的決策支持。對糖尿病心血管并發(fā)癥的臨床早期診斷具有一定的現(xiàn)實意義。
[Abstract]:Objective: Taking the diabetic patients as the research object, using the advanced database development platform to obtain the clinical information of the patients with diabetes, the basic information and the establishment of the database by collecting the original configuration and functional data of echocardiography, according to the principle of data mining (Data Mining, DM), and using data mining tools for the diabetes of large samples The clinical data of the patients and the data of echocardiography related to cardiac function were excavated, and the key influencing factors and characteristic indexes of the changes of cardiac function (left ventricular diastolic function) were obtained, and the potential, valuable rules between the factors and the changes of cardiac function were revealed, and the changes between the indexes were analyzed. Regularity, understand the dynamic changes of cardiac function of diabetes, predict the changes of diabetic cardiac function through the establishment of data model and provide the feasible decision support for the early intervention, dynamic monitoring, clinical treatment and therapeutic observation of diabetic cardiac complications.
Methods: from July 2012 to February 2014, 360 patients with diabetes mellitus were diagnosed by echocardiography in our hospital and 360 cases of diabetes have been diagnosed. The high grade color Doppler ultrasonic diagnostic instrument was used in accordance with the unified and standardized examination, and the operation was carried out to obtain the cardiac structure, function ultrasound data and record the height of the subjects. Body weight, abdominal circumference, body surface area and other physical indicators, through the hospital information system (hospital informationsystem, HIS) access to access the clinical information and basic information of diabetes patients (patients have no diabetes family history, blood sugar, blood lipids, blood pressure, high sugar, high calorie diet, high protein diet, smoking, whether or not drinking, and The diabetes heart function database was set up with the above data sources. SQL Server2008 was used as the database management tool. The basic information of diabetic patients, the clinical information and the ultrasonic data reflecting the heart function were excavated with the SQL Server2008 data mining tool, and the influencing factors were excavated. With the potential and valuable rules of the changes in cardiac function (left ventricular diastolic function), the changes in the changes in the ground function (left ventricular diastolic function) of diabetic patients were analyzed, and a simple model for the changes of cardiac function (left ventricular diastolic function) in diabetic patients was preliminarily designed.
Results: the basic information, clinical information and the relationship database of cardiac configuration and functional data were established, and the relational database was preprocessed into a transaction database suitable for data mining, and a preliminary design of the cardiac function (left ventricular diastolic function) of diabetic patients was preliminarily designed by data mining. The establishment of an over functional data model predicts the changes in diabetic cardiac function and provides a feasible decision support for the early intervention of diabetic cardiac complications, dynamic monitoring, clinical treatment, and therapeutic observation. Through data mining, we can obtain diabetes heart function change and genetic history of diabetes, blood sugar, blood pressure, blood lipid, BMI and abdominal circumference, left atrial volume index and so on. We can establish a data model that reflects the changes of left ventricular diastolic function in diabetic patients.
Conclusion: the use of data mining technology can effectively excavate a large number of medical information. It can extract valuable rules and acquire knowledge. It can predict the changes of cardiac function in time and accurately. It can provide the feasibility of early intervention, dynamic monitoring, clinical treatment and observation of curative effect of diabetic cardiac complications. Policy support is of practical significance for the early diagnosis of diabetic cardiovascular complications.
【學(xué)位授予單位】：皖南醫(yī)學(xué)院
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：R587.1;R445.1

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