Effective Liver Cancer Diagnosis Method based on Machine Learning Algorithm

被引：0

作者：

Kim, Sangman ^{[1
]}

Jung, Seungpyo ^{[1
]}

Park, Youngju ^{[1
]}

Lee, Jihoon ^{[1
]}

Park, Jusung ^{[1
]}

机构：

[1] Pusan Natl Univ, Dept Elect & Elect Engn, Pusan 609735, South Korea

来源：

2014 7TH INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI 2014) | 2014年

关键词：

component; neural network; fuzzy neural network; machine learning; diagnosis; select-drop; feature; FUNDAMENTALS; NETWORK;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In this paper, we introduce a method to find useful markers from sensor arrays which have massive sensing points and diagnose liver cancer based on machine learning algorithms which are neural network and fuzzy neural network. We obtain reliable results by using a learning ability and n-fold cross validation. For the verification of the proposed method, raw data of serums from 314 normal and 81 patients reacted to 1,142 aptamers are used. According to the results, we can detect liver cancer with the accuracy of 99.19 % by average use of 132 aptamers based on neural network and 98.19 % by average use of 226 aptamers based on fuzzy neural network.

引用

页码：714 / 718

页数：5

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