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Prediction of Liver Cancer Development Risk in Genotype 4 Hepatitis C Patients using Knowledge Discovery Modeling

机译:利用知识发现建模预测基因型4丙型肝炎患者肝癌发育风险

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Hepatitis C is a primary reason for the liver cancer, which is a leading cause of death. The objective of this paper is to predict the hepatitis C infection progression into cirrhosis or liver cancer. For the prediction of the disease progression, a knowledge discovery framework is proposed consisting of three phases: preprocessing, data mining and prediction. While the preprocessing phase focuses on the discretization of the training data, the data mining phase focuses on mining patients' records using a rule based classifier built by the proposed algorithm to generate a set of unique rules. Eventually, the predictor uses the rules to predict patients' disease progression. Experimentation on 1908 chronic hepatitis C Egyptian patients with 27 extracted features collected from blood samples were used to train the model, with other 406 patients' cases for testing which showed accuracy 99.5%.
机译:丙型肝炎是肝癌的主要原因,这是一种死亡的主要原因。本文的目的是预测丙型肝炎感染进入肝硬化或肝癌。为了预测疾病进展,提出了一种由三个阶段组成的知识发现框架:预处理,数据挖掘和预测。虽然预处理阶段侧重于培训数据的离散化,但数据挖掘阶段使用由所提出的算法构建的基于规则的分类器来创建患者的记录来生成一组唯一的规则。最终,预测指标使用规则来预测患者的疾病进展。 1908年的慢性丙型肝炎患有来自血液样本收集的27例提取特征的慢性丙型肝炎患者用于培训模型,其他406名患者的检测案例,表现出准确性为99.5%。

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