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A Comparative Study of Survival approaches for Breast Cancer Patients

机译：乳腺癌患者生存方法的比较研究

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A survival analysis model leads one to analyze main factors which impact a patient's therapy process. In practice a survival analysis is capable of affecting therapeutic protocols. Different methods have been approached to analyze the survival of a breast cancer patient by researchers. The objective of this research is to lead specialists analyzing the breast cancer patients effectively. This research by analyzing 2010 breast cancer patients 1) attempts to propose six different statistical models using parametric and semi-parametric approaches for survival analysis of breast cancer patients, 2) compares the performance capabilities of the proposed statistical models analytically, and 3) addresses the most superior approach for a survival analysis of a breast cancer. To analyze the capability of the six proposed models Akaike term is used. This comprehensive research also indicates that the hazard factors commonly proposed in literature are not capable of leading a specialist to analyze the survival completely. Although it is possible to model the breast cancer survival using different approaches, this research reveals the proposed semi parametric model is capable of providing the most superior condition. The capability of the best parametric model among the five proposed parametric models of this comprehensive research is also addressed. Kaplan-Meier diagram is used to analyze the importance of two new hazard factors proposed in this paper.
机译：生存分析模型可以分析影响患者治疗过程的主要因素。在实践中，生存分析能够影响治疗方案。研究人员采用了不同的方法来分析乳腺癌患者的生存情况。这项研究的目的是带领专家有效地分析乳腺癌患者。这项研究通过分析2010年的乳腺癌患者1）尝试使用参数和半参数方法提出六个不同的统计模型，用于乳腺癌患者的生存分析; 2）尝试比较所提出的统计模型的性能，并3）解决乳腺癌生存分析的最佳方法。为了分析所提出的六个模型的能力，使用了Akaike项。这项全面的研究还表明，文献中通常提出的危险因素无法使专家完全分析其生存率。尽管可以使用不同的方法对乳腺癌的生存进行建模，但这项研究表明所提出的半参数模型能够提供最优越的条件。还讨论了在这项全面研究的五个建议参数模型中最佳参数模型的能力。 Kaplan-Meier图用于分析本文提出的两个新危险因素的重要性。

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