All Title Author
Keywords Abstract

Publish in OALib Journal
ISSN: 2333-9721
APC: Only $99

ViewsDownloads

Relative Articles

More...

基于Kaplan-Meier与Cox的口腔鳞状细胞癌患者数据分析
Data Analysis of Patients with Oral Squamous Cell Carcinoma Based on Kaplan-Meier and Cox

DOI: 10.12677/HJDM.2022.121006, PP. 43-48

Keywords: 医疗大数据,Kaplan-Meier,Cox模型,比例风险假设
Big Data in Healthcare
, Kaplan-Meier, Cox Model, Proportional Risk Assumption

Full-Text   Cite this paper   Add to My Lib

Abstract:

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。
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.

References

[1]  医疗大数据存在的问题[EB/OL]. https://www.docin.com/p-1966055788.html, 2021-10-01.
[2]  李雪迎. 画说统计|生存分析之Kaplan-Meier曲线都告诉我们什么[EB/OL]. http://www.360doc.com/content/17/0626/11/6175644_666623573.shtml, 2021-10-01.
[3]  Cui, E., Leroux, A., Smir-nova, E. and Crainiceanu, C.M. (2021) Fast Univariate Inference for Longitudinal Functional Models. Journal of Com-putational and Graphical Statistics, 1-12.
[4]  王定坤, 杨杉. 基于COX比例风险模型分析心力衰竭影响因素[J]. 电脑知识与技术, 2021, 17(24): 33-35.
[5]  李清河, 江泽平. 白刺研究(Research on Plant Species of Genus Nitraria L)[M]. 北京: 中国林业出版社, 2011: 102.

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413