Objective To explore the application of BP neural network in the survival analysis.
目的探讨BP神经在生存分析中的应用。
Objective To introduce explained variation and its application in survival analysis.
目的介绍生存分析中解释变异度量及其应用。
Made a analysis of risk factor of stoma fistula, infection and death. and a survival analysis.
对并发症吻合口瘘、术区感染、死亡的危险因素作单因素及多因素分析。
Conclusion: the accelerated failure-time model has good applicability in the area of survival analysis.
结论：加速失效时间模型在生存分析领域具有良好的适用性。
Methods: to study factors of influence survival time with multivariate analysis.
方法采用多因素分析的方法研究影响生存时间的因素。
Univariate analysis found that the size of tumor, TNM stage were related to survival rates.
单因素分析表明：临床分期、肿瘤大小是局部晚期乳腺癌的生存指标。
Patient actuarial survival was determined by Kaplan-Meier analysis.
采用荟萃分析精确计算了患者的生存率。
The primary endpoint was overall survival, and analysis was done by intention to treat.
主要终点指标为总生存期，资料分析采用意向处理分析。
This survival difference persisted after multiple logistic regression analysis.
在多元分析后，二者之间的不同仍在持续。
This survival difference persisted after multiple logistic regression analysis.
在多元分析后，二者之间的不同仍在持续。
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