Restricted Boltzmann Machines for Classification of Hepatocellular Carcinoma

Joint Authors

Dai, Liping
Zhang, Jian-Ying
Koziol, James A.
Ren, Pengfei
Tan, Eng M.

Source

Computational Biology Journal

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

Biology

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