A Novel CAD System for Detection and Classification of Liver Cirrhosis using Support Vector Machine and Artificial Neural Network

被引：0
|
作者：
Al-Shabi, M. A. [1 ]
机构：
[1] Taibah Univ, Coll Business Adm, Dept Management Informat Syst, Medina, Saudi Arabia
来源：
INTERNATIONAL JOURNAL OF COMPUTER SCIENCE AND NETWORK SECURITY | 2019年 / 19卷 / 08期
关键词：
Liver Cirrhosis; Artificial Neural Network; Support Vector Machine; Accuracy;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, a computer aided system is designed to determine the extent to which the blood indices, fibro-scan and liver biopsy can help diagnose liver cirrhosis in patients with Chronic Hepatitis C. A novel approach, for feature selection is created and used to reduce the extracted features to their best informative subset. The performance of three classifiers is investigated. One is the Support Vector Machine (SVM) with cross-validation, the second is a Multilayer Perception neural network (MLP), and the third is Generalized Regression Neural Network (GRNN). The system resulted in an accuracy of 100% in both training and validation phases for SVM and MLP and 99.50 % for GRNN.
引用
收藏
页码：18 / 23
页数：6
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