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A Review of Feature Selection

Year: 2024

Type: article

Abstract: Feature selection is a preprocessing technique that identifies the salient features of a given scenario. It has been used in the past for a wide range of problems, including intrusion detection systems, financial problems, and the analysis of biological data. Feature selection has been especially useful in medical applications, where it may help identify the underlying reasons for an illness in addition to reducing dimensionality. We provide some basic concepts of medical applications and the necessary background information on feature selection. We review the most recent feature selection methods developed for and applied to medical problems, covering a broad spectrum of applications including medical imaging, DNA microarray data analysis, and biomedical signal processing. A case study of two medical applications utilizing actual patient data is used to demonstrate the usefulness of applying feature selection techniques to medical challenges and to highlight how these methods function in practical scenarios.

Source: Journal of Optimization in Soft Computing (JOSC) بهينه سازي در محاسبات نرم

DOI: 10.82553/josc.2025.140309071191740

Authors: Abdollahi, Jafar, Nouri-Moghaddam, Babak, Mikaeilvand, Naser, Jahanbakhsh Gudakahriz, Sajjad, Khosravani, Ailin, Mirzaei, Abbas

Institutions: Islamic Azad University Ardabil, Islamic Azad University, Tehran, Islamic Azad University Central Tehran Branch

Language: English

Topic: Gene expression and cancer classification

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: hybrid

OpenAlex ID: W6921828009

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