A Novel Hybrid Runge Kutta Optimizer with Support Vector Machine on Gene Expression Data for Cancer Classification

A Novel Hybrid Runge Kutta Optimizer with Support Vector Machine on Gene Expression Data for Cancer Classification

It is crucial to accurately categorize cancers using microarray data. Researchers have employed a variety of computational intelligence approaches to analyze gene expression data. It is believed that the most difficult part of the problem of cancer diagnosis is determining which genes are informativ...

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Bibliographic Details
Main Authors: Essam H. Houssein, Hager N. Hassan, Nagwan Abdel Samee, Mona M. Jamjoom
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Diagnostics
Subjects:
feature selection
Runge Kutta optimizer
microarray
gene expression
support vector machines
cancer classification
Online Access:https://www.mdpi.com/2075-4418/13/9/1621

Internet

https://www.mdpi.com/2075-4418/13/9/1621

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