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Machine Learning Algorithm Early Detection of Liver Cancer: A Review

by Simran Jain, Madan Lal Saini
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 6
Year of Publication: 2022
Authors: Simran Jain, Madan Lal Saini
10.5120/ijca2022922018

Simran Jain, Madan Lal Saini . Machine Learning Algorithm Early Detection of Liver Cancer: A Review. International Journal of Computer Applications. 184, 6 ( Apr 2022), 42-47. DOI=10.5120/ijca2022922018

@article{ 10.5120/ijca2022922018,
author = { Simran Jain, Madan Lal Saini },
title = { Machine Learning Algorithm Early Detection of Liver Cancer: A Review },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2022 },
volume = { 184 },
number = { 6 },
month = { Apr },
year = { 2022 },
issn = { 0975-8887 },
pages = { 42-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number6/32336-2022922018/ },
doi = { 10.5120/ijca2022922018 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:20:48.276553+05:30
%A Simran Jain
%A Madan Lal Saini
%T Machine Learning Algorithm Early Detection of Liver Cancer: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 6
%P 42-47
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the most highly prevalent cancers today is liver cancer.The segmentation of a liver tumour is a critical step in making an early detection and recommending a treatment. It has always been tedious to segment data by hand, so cancer detection techniques now use a variety of machine learning algorithms, such as decision trees, Support Vector machine, artificial neural networks, random forests, Logistic Regressions and genetic algorithms. These algorithms are all used in the cancer detection process. The purpose of this review article is to conduct a comprehensive and comparative analysis of machine learning algorithms for diagnosing and predicting liver cancer in the medical field, which have already been used to predict liver disease by a number of authors, and to highlight the most frequently used features, classifiers, techniques, fundamental ideas, and accuracy.

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Index Terms

Computer Science
Information Sciences

Keywords

Machine Learning Liver Cancer Feature Selection Accuracy

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