A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression

Year : 2025 | Volume : 03 | 02 | Page :
    By

    Veerpal kaur,

  • Jasvir Singh,

  • Neelofar Sohi,

  1. Research Scholar, Department of Computer Science and Engineering Punjabi University Patiala, Punjab, India
  2. Assistant Professor, Department of Computer Science and Engineering Punjabi University Patiala, Punjab, India
  3. Assistant Professor, Department of Computer Science and Engineering Punjabi University Patiala, Punjab, India

Abstract

Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms for identifying Leukemia subtypes such as AML (Acute Myeloid Leukemia) and ALL (Acute Lymphoblastic Leukemia). Several models such as Support Vector Machines, k-Nearest Neighbors, Artificial Neural Networks, Deep Neural Networks, and ensemble learning methods have been discussed for their accuracy and effectiveness in handling high-dimensional microarray datasets. Moreover, feature selection techniques like Genetic Algorithms, Particle Swarm Optimization, and recent hybrid models such as ACO-ALO and SCBAO are reviewed for enhancing classification accuracy. Recent advancements also incorporate entropy-based and multi-class feature extraction to improve performance. While these approaches demonstrate high precision in classification, challenges such as limited datasets, computational cost, and clinical validation remain. The review highlights the potential of hybrid and integrative models for robust and scalable Leukemia diagnosis, emphasizing the need for continued research to bridge computational advancements with clinical applicability.

Keywords: Microarray, Gene Expression, Leukemia, Acute myeloid leukemia, Acute Lymphoblastic Leukemia.

How to cite this article:
Veerpal kaur, Jasvir Singh, Neelofar Sohi. A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression. International Journal of Genetic Modifications and Recombinations. 2025; 03(02):-.
How to cite this URL:
Veerpal kaur, Jasvir Singh, Neelofar Sohi. A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression. International Journal of Genetic Modifications and Recombinations. 2025; 03(02):-. Available from: https://journals.stmjournals.com/ijgmr/article=2025/view=224795


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Ahead of Print Subscription Review Article
Volume 03
02
Received 27/04/2025
Accepted 13/08/2025
Published 23/08/2025
Publication Time 118 Days
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