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Restricted Boltzmann Machines for Classification of Hepatocellular Carcinoma
Joint Authors
Dai, Liping
Zhang, Jian-Ying
Koziol, James A.
Ren, Pengfei
Tan, Eng M.
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-14
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Abstract EN
Multiple antigen miniarrays can provide accurate tools for cancer detection and diagnosis.
These miniarrays can be validated by examining their operating characteristics in classifying individuals as either cancer patients or normal (non-cancer) subjects.
We describe the use of restricted Boltzmann machines for this classification problem, relative to diagnosis of hepatocellular carcinoma.
In this setting, we find that its operating characteristics are similar to a logistic regression standard and suggest that restricted Boltzmann machines merit further consideration for classification problems.
American Psychological Association (APA)
Koziol, James A.& Tan, Eng M.& Dai, Liping& Ren, Pengfei& Zhang, Jian-Ying. 2014. Restricted Boltzmann Machines for Classification of Hepatocellular Carcinoma. Computational Biology Journal،Vol. 2014, no. 2014, pp.1-5.
https://search.emarefa.net/detail/BIM-470606
Modern Language Association (MLA)
Koziol, James A.…[et al.]. Restricted Boltzmann Machines for Classification of Hepatocellular Carcinoma. Computational Biology Journal No. 2014 (2014), pp.1-5.
https://search.emarefa.net/detail/BIM-470606
American Medical Association (AMA)
Koziol, James A.& Tan, Eng M.& Dai, Liping& Ren, Pengfei& Zhang, Jian-Ying. Restricted Boltzmann Machines for Classification of Hepatocellular Carcinoma. Computational Biology Journal. 2014. Vol. 2014, no. 2014, pp.1-5.
https://search.emarefa.net/detail/BIM-470606
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-470606