%0 Journal Article
%T 基于Kaplan-Meier与Cox的口腔鳞状细胞癌患者数据分析<br>Data Analysis of Patients with Oral Squamous Cell Carcinoma Based on Kaplan-Meier and Cox
%A 黄钰凝
%J Hans Journal of Data Mining
%P 43-48
%@ 2163-1468
%D 2022
%I Hans Publishing
%R 10.12677/HJDM.2022.121006
%X 临床医疗事业是大数据发展及应用中重要的一个方面。本文以口腔鳞状癌患者的数据作为基础，通过对生存分析(Kaplan-Meier)曲线和对患者观察的数据进行挖掘，探究出影响因素与生存时间和结局的关系，再通过Cox回归模型对风险率进行预测，实现了研究各个因素对生存概率的重要性。该模型可用于临床医疗对口腔鳞状癌症的研究。<br />
Clinical medical career is an important aspect of the development and application of big data. In this paper, using data from patients with oral squamous carcinoma as a basis, we explored the relation-ship between the three of influencing factors, survival time and outcome by mining survival analysis (Kaplan-Meier) curves and data from patient observation, and then predicted the risk rate by Cox regression model, and achieved to study the importance of each factor on survival probability. This model can be used in clinical care for the study of oral squamous cancer.
%K 医疗大数据，Kaplan-Meier，Cox模型，比例风险假设<br>Big Data in Healthcare
%K Kaplan-Meier
%K Cox Model
%K Proportional Risk Assumption
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=48216