Hiroyuki Ogihara, Y. Fujita, Y. Hamamoto, N. Iizuka, M. Oka
{"title":"Classification Based on Boolean Algebra and Its Application to the Prediction of Recurrence of Liver Cancer","authors":"Hiroyuki Ogihara, Y. Fujita, Y. Hamamoto, N. Iizuka, M. Oka","doi":"10.1109/ACPR.2013.152","DOIUrl":null,"url":null,"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.","PeriodicalId":365633,"journal":{"name":"2013 2nd IAPR Asian Conference on Pattern Recognition","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 2nd IAPR Asian Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACPR.2013.152","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.