Hepatocellular Carcinoma Detection Using Machine Learning Techniques

被引：4
|
作者：
Angelis, Ioannis [1 ]
Exarchos, Themis [1 ]
机构：
[1] Ionian Univ, Dept Informat, Corfu, Greece
来源：
GENEDIS 2020: COMPUTATIONAL BIOLOGY AND BIOINFORMATICS | 2021年 / 1338卷
关键词：
Hepatocellular carcinoma; Machine learning; Classification;
D O I：
10.1007/978-3-030-78775-2_4
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
Hepatocellular carcinoma (HCC) is a form of primary cancer appearing in the liver. In this work used the hepatocellular carcinoma data-set from the UCI machine learning repository and tested different techniques for feature selection and classification. The following algorithms were used: decision trees, random forests, SVMs, k-NN classifiers, AdaBoost, and gradient boost. The best results were obtained using gradient boost with 84% accuracy and 93% precision. Finally, we deployed the model to a web application as a decision support system for clinicians.
引用
收藏
页码：21 / 29
页数：9
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