Local Entropy Based Remora Optimization and Sparse Autoencoders for Cancer Diagnosis Through Microarray Gene Expression Analysis

Local Entropy Based Remora Optimization and Sparse Autoencoders for Cancer Diagnosis Through Microarray Gene Expression Analysis

Gene expression analysis can be used as a tool to detect cancer and the type of cancer in its early stages. However, the computational complexity for gene expression analysis is quite high due to the large amount of numerical data. Hence, dimensionality reduction techniques are employed to reduce th...

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Bibliographic Details
Main Authors: N. Bharanidharan, S. R. Sannasi Chakravarthy, Vinoth Kumar Venkatesan, Mohamed Abbas, T. R. Mahesh, E. Mohan, Krishnamoorthy Venkatesan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Cancer
entropy
sparse autoencoder
remora optimization
dimensionality reduction
deep learning
Online Access:https://ieeexplore.ieee.org/document/10453518/

Internet

https://ieeexplore.ieee.org/document/10453518/

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