Classification of Kidney Cancer Data Using Cost-Sensitive Hybrid Deep Learning Approach

Classification of Kidney Cancer Data Using Cost-Sensitive Hybrid Deep Learning Approach

Recently, large-scale bioinformatics and genomic data have been generated using advanced biotechnology methods, thus increasing the importance of analyzing such data. Numerous data mining methods have been developed to process genomic data in the field of bioinformatics. We extracted significant gen...

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Bibliographic Details
Main Authors: Ho Sun Shon, Erdenebileg Batbaatar, Kyoung Ok Kim, Eun Jong Cha, Kyung-Ah Kim
Format: Article
Language:English
Published: MDPI AG 2020-01-01
Series:Symmetry
Subjects:
data mining
machine learning
kidney cancer
bioinformatics
autoencoder
neural network
cost-sensitive
hybrid deep learning
cancer classification
Online Access:https://www.mdpi.com/2073-8994/12/1/154

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https://www.mdpi.com/2073-8994/12/1/154

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