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首页> 外文期刊>International journal of soft computing >Prediction of Post-Surgical Survival of Lung Cancer Patients after Thoracic Surgery using Data Mining Techniques
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Prediction of Post-Surgical Survival of Lung Cancer Patients after Thoracic Surgery using Data Mining Techniques

机译:利用数据挖掘技术预测胸外科术后肺癌患者的外科生存

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摘要

Lung cancer is one of the common forms of cancer in today’s world. Majority of lung cancers can be diagnosed and cured. Consumption of tobacco is the major reason for lung cancer. Lung cancers are categorized as small cell and non-small cell cancers. Thoracic surgery is one of the way to diagnose lung cancer if it is detected at an early stage. Hence, it is better to cure lung cancer at the beginning stage. Patients survival cannot be predicted by the surgery alone. Hence if the patient’s survival cannot be extended for a year after surgery, then the factors for the death remains a mystery. In order to overcome this problem, we have used data mining techniques in this paper to detect the patient’s survival. The main objective of this paper is to correlate and evaluate various data mining algorithms on predicting the survival of lung cancer patients after thoracic surgery. This study also explains about a new methodology by combining data mining algorithms for the prediction. This paper also explains the factors that are responsible for the death of the patients after thoracic surgery.
机译:肺癌是当今世界中常见的癌症形式之一。大多数肺癌可以被诊断和治愈。烟草消耗是肺癌的主要原因。肺癌被分类为小细胞和非小细胞癌。如果在早期检测到,胸部手术是诊断肺癌的方法之一。因此,最好在开始阶段治愈肺癌。单独的手术不能预测患者存活。因此,如果手术后患者的存活率不能延长一年,那么死亡的因素仍然是一个谜。为了克服这个问题,我们在本文中使用了数据挖掘技术来检测患者的生存。本文的主要目的是关联和评估各种数据挖掘算法,以预测胸外科肺癌患者存活。本研究还通过组合数据挖掘算法来解释新方法来解释预测的数据挖掘算法。本文还解释了胸部手术后患者死亡的因素。

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