利用知识发现模型预测基因4型丙型肝炎患者肝癌发生风险

Tasneem A. Gameel, S. Rady, Khaled El-Bahnasy, S. Kamal
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引用次数: 6

摘要

丙型肝炎是导致肝癌的主要原因,而肝癌是导致死亡的主要原因。本文的目的是预测丙型肝炎感染进展为肝硬化或肝癌。针对疾病进展的预测,提出了一个由预处理、数据挖掘和预测三个阶段组成的知识发现框架。预处理阶段侧重于训练数据的离散化,而数据挖掘阶段侧重于使用算法构建的基于规则的分类器挖掘患者记录,以生成一组独特的规则。最终,预测器使用这些规则来预测患者的疾病进展。以埃及1908例慢性丙型肝炎患者为实验对象,从血样中提取27个特征进行训练,并对406例患者进行测试,准确率达到99.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of liver cancer development risk in genotype 4 hepatitis C patients using knowledge discovery modeling
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 %.
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