本文選題：股骨頸骨折 + 決策樹C4.5��； 參考：《太原理工大學(xué)》2017年碩士論文

【摘要】：股骨頸骨折手術(shù)預(yù)后質(zhì)量評(píng)分(Harris評(píng)分)是骨科大夫極其關(guān)心的問題。隨著病例的積累,我們希望通過病例信息找到影響Harris評(píng)分的重要因子,并使用這些影響因子對(duì)新患者的手術(shù)預(yù)后Harris評(píng)分類別進(jìn)行預(yù)測。貝葉斯網(wǎng)絡(luò)分類器是基于概率論與圖論的分類網(wǎng)絡(luò),具有優(yōu)良的分類功能,已廣泛應(yīng)用于數(shù)據(jù)挖掘、統(tǒng)計(jì)分析和人工智能等領(lǐng)域。決策樹是一種基于信息增益理論的分類算法,是一種使用簡單且應(yīng)用面廣泛的分類器。本文從數(shù)據(jù)挖掘的概述出發(fā),首先,敘述了數(shù)據(jù)挖掘的基本內(nèi)容及發(fā)展趨勢;進(jìn)一步介紹了決策樹C4.5算法和貝葉斯網(wǎng)絡(luò)分類器算法并提出了決策樹C4.5算法的優(yōu)化算法——決策樹L-C4.5算法;最后,將決策樹L-C4.5算法和貝葉斯網(wǎng)絡(luò)分類器算法應(yīng)用于股骨頸預(yù)后評(píng)分分類數(shù)據(jù)并成功搭建了優(yōu)良的股骨頸手術(shù)預(yù)后評(píng)分的決策樹和貝葉斯網(wǎng)絡(luò)分類器。在此基礎(chǔ)上,發(fā)現(xiàn)了Harris評(píng)分的重要影響因子分別為:BMI指數(shù)、骨折類型是否為Garden分型、是否存在糖尿病史、否是為側(cè)位螺釘平行結(jié)構(gòu)、骨折位置是否為三角結(jié)構(gòu)及骨折類別。
[Abstract]:The prognosis quality score of femoral neck fracture (Harris score) is of great concern to orthopedic doctors. With the accumulation of cases, we hope to find out the important factors that affect the Harris score through the case information, and use these factors to predict the Harris score of the surgical prognosis of the new patients. Bayesian network classifier is a classification network based on probability theory and graph theory. It has excellent classification function and has been widely used in data mining, statistical analysis and artificial intelligence. Decision tree is a classification algorithm based on information gain theory. It is a simple and widely used classifier. This paper starts from the summary of data mining, first of all, describes the basic content and development trend of data mining; Furthermore, the decision tree C4.5 algorithm and Bayesian network classifier algorithm are introduced, and the decision tree L-C4.5 algorithm, which is the optimization algorithm of decision tree C4.5 algorithm, is proposed. The decision tree L-C4.5 algorithm and Bayesian network classifier algorithm are applied to the classification data of femoral neck prognosis score, and the excellent decision tree and Bayesian network classifier for the prognosis score of femoral neck surgery are successfully constructed. On this basis, it was found that the important influencing factors of Harris score were the Harris index, whether the fracture type was Garden classification, whether there was diabetes history, whether it was a lateral screw parallel structure, whether the fracture position was triangular structure and fracture type.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP311.13

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相關(guān)期刊論文 前10條

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本文編號(hào)：1841657