A novel machine learning approach for early detection of hepatocellular carcinoma patients
Authors:
- Wojciech Książek,
- Moloud Abdar,
- U. Rajendra Acharya,
- Paweł Pławiak
Abstract
Liver cancer is quite common type of cancer among individuals worldwide. Hepatocellular carcinoma (HCC) is the malignancy of liver cancer. It has high impact on individual’s life and investigating it early can decline the number of annual deaths. This study proposes a new machine learning approach to detect HCC using 165 patients. Ten well-known machine learning algorithms are employed. In the preprocessing step, the normalization approach is used. The genetic algorithm coupled with stratified 5-fold cross-validation method is applied twice, first for parameter optimization and then for feature selection. In this work, support vector machine (SVM) (type C-SVC) with new 2level genetic optimizer (genetic training) and feature selection yielded the highest accuracy and F1-Score of 0.8849 and 0.8762 respectively. Our proposed model can be used to test the performance with huge database and aid the clinicians.
- Record ID
- CUT7847aca496b645c79f882c1f0685f01a
- Publication categories
- ;
- Author
- Journal series
- Cognitive Systems Research, ISSN 2214-4366, e-ISSN 1389-0417
- Issue year
- 2019
- Vol
- 54
- Pages
- 116-127
- Other elements of collation
- schem.; tab.; wykr.; Bibliografia (na s.) - 125-127; Oznaczenie streszczenia - Abstr.; Numeracja w czasopiśmie - Vol. 54
- Keywords in English
- machine learning, data mining, hepatocellular carcinoma (HCC), genetic algorithm, normalization, feature selection
- DOI
- DOI:10.1016/j.cogsys.2018.12.001 Opening in a new tab
- URL
- https://www.sciencedirect.com/science/article/pii/S1389041718308714 Opening in a new tab
- Language
- eng (en) English
- Score (nominal)
- 70
- Publication indicators
- Citation count
- 120
- Additional fields
- Indeksowana w: Web of Science, Scopus
- Uniform Resource Identifier
- https://cris.pk.edu.pl/info/article/CUT7847aca496b645c79f882c1f0685f01a/
- URN
urn:pkr-prod:CUT7847aca496b645c79f882c1f0685f01a
* presented citation count is obtained through Internet information analysis, and it is close to the number calculated by the Publish or PerishOpening in a new tab system.