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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:癌症在造成全世界的发病和死亡率方面发挥着主导作用。已经开发了几种治疗方法,并练习抗癌。完全可植入的静脉内接入口药物供应(胸部)治疗是一种新方法,采用完全可植入的静脉接入口(TiVAP)递送方法,是一种具有较低副作用的鞘内药物输送系统(IDD),以提高患者的生活质量。本文报道了我们的研究旨在评估Tivapds治疗的有效性,以便在中国概括这种治疗的贡献。我们的数据样本来自苏州大学第二附属医院,在中国的Tivapds实践的先行者以及患者的协议。分析数据统计摘要结果和每个两个识别属性之间的关系。基于结果,采用了2个采用C4.5决策树和逻辑回归算法的预测模型进行预测。结果用作评估个体治疗病例的参考,从而可以实现治疗的有效性,如果可能的话,以提高Tivapds治疗的效率。

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