Classification Based on Boolean Algebra and Its Application to the Prediction of Recurrence of Liver Cancer

Hiroyuki Ogihara, Y. Fujita, Y. Hamamoto, N. Iizuka, M. Oka
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引用次数: 3

Abstract

Liver cancer has a high likelihood of recurrence despite complete surgical resection and is thus known as an intractable cancer. If postoperative recurrence of cancer is correctly predicted for each patient as a form of personalized medicine, effective treatment can be carried out. The purpose of this paper is to investigate prediction of recurrence of liver cancer by use of blood test data only in patients who underwent complete surgical resection of liver cancer. For this purpose, we propose a classifier based on Boolean algebra using a binary pattern consisting of a combination of clinical and genomic data by which we can predict recurrence of liver cancer. We perform a predictive experiment using data from patients with recurrence and non-recurrence and discuss the effectiveness of the proposed method from the experimental results.
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基于布尔代数的分类及其在肝癌复发预测中的应用
肝癌有很高的复发可能性,尽管完全手术切除,因此被称为难治性癌症。如果对每个患者的癌症术后复发进行正确的预测,作为个性化医疗的一种形式,就可以进行有效的治疗。本文的目的是研究仅在肝癌手术完全切除的患者中使用血液检查数据预测肝癌复发。为此,我们提出了一个基于布尔代数的分类器,使用由临床和基因组数据组合组成的二进制模式,我们可以通过它来预测肝癌的复发。我们使用复发和非复发患者的数据进行了预测实验,并从实验结果讨论了所提出方法的有效性。
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