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New Cancer Treatment Evaluation through Big Data Analytics

机译:通过大数据分析进行新的癌症治疗评估

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Cancer plays a leading role in causing morbidity and mortality worldwide. Several treatments have been developed and practiced for fighting against cancer. Totally Implantable Venous Access Port Drug Supply (TIVAPDS) treatment is a new method utilizing Totally Implantable Venous Access Port (TIVAP) delivery method, which is one kind of Intrathecal Drug Delivery System (IDD) with lower side effects, to increase patient's quality of life. This paper reports our study aiming to evaluate the effectiveness of TIVAPDS treatment in order to make contributions to generalize this treatment in China. Our data samples come from The Second Affiliated Hospital of Suzhou University, a forerunner of TIVAPDS practices in China and with patients' agreement. The data statistics summary results and the relationships between each two identified attributes are analyzed. Based on the results, 2 predictive models utilizing C4.5 decision tree and logistic regression algorithms are adopted for prediction. The results are used as reference to assess individual treatment cases, so that the effectiveness of the treatment can be achieved and if possible, to improve the efficiency of TIVAPDS treatment.
机译:癌症在引起全世界发病率和死亡率方面起着主导作用。已经开发和实践了几种抗癌治疗方法。完全植入式静脉通路药物供应(TIVAPDS)治疗是一种利用完全植入式静脉通路药物(TIVAP)输送方法的新方法,该方法是一种副作用较小的鞘内药物输送系统(IDD),旨在提高患者的生活质量。 。本文报告了我们的研究,旨在评估TIVAPDS治疗的有效性,以便为在中国推广这种治疗做出贡献。我们的数据样本来自苏州大学第二附属医院,这是中国TIVAPDS实践的先驱,并且得到了患者的同意。数据统计摘要结果以及每两个标识的属性之间的关系都进行了分析。根据结果​​,采用2个利用C4.5决策树和logistic回归算法的预测模型进行预测。结果可作为评估个别治疗案例的参考,从而可以达到治疗的效果,并在可能的情况下提高TIVAPDS治疗的效率。

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