Machine learning-based liver cancer classification using gene expression microarray data

Mahmoud, Amena and Meraj, Syeda Shaizadi and Saini, Shilpa and Juneja, Sapna and Talpur, Kazim Raza and Shah, Asadullah and Ahmed, Wesam (2025) Machine learning-based liver cancer classification using gene expression microarray data. In: 9th International Conference on Engineering Technologies and Applied Sciences (ICETAS2024), 25th August 2025, Bahrain.

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Abstract

Detecting a liver tumor early and accurately can save lives because the liver is an important and multifunctional human organ. Machine learning algorithms have recently emerged as effective tools for enhancing liver cancer categorization using gene expression microarray data. This study proposes a supervised machine learning-based approach for liver cancer diagnosis that influences gene expression profiles to achieve an accurate diagnosis. A large sample size is crucial to be obtained and leads to a precise and reliable outcome. In this research, we combine multiple datasets from the Curated Microarray (CuMiDa) Database with the same features and use machine-learning models. Random forest (RF) model, SVM model, Xgboost model, K-nearest neighbor (KNN) model, and Decision tree (DT) model, and are used as classification models for classifying liver cancer using gene expressions. The results indicate that effect size and classification accuracies increase, while variances in effect size shrink with the increase in sample size. The results reveal that the RF model has better accuracy of 96.55%.

Item Type:	Proceeding Paper (Other)
Additional Information:	6566/123207
Uncontrolled Keywords:	Liver Cancer Classification; Machine learning; Gene Expression Microarray Bioinformatics
Subjects:	T Technology > T Technology (General) > T10.5 Communication of technical information
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology > Department of Information System Kulliyyah of Information and Communication Technology Kulliyyah of Information and Communication Technology
Depositing User:	Prof Asadullah Shah
Date Deposited:	17 Sep 2025 14:31
Last Modified:	17 Sep 2025 14:34
URI:	http://irep.iium.edu.my/id/eprint/123207

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