Restricted Boltzmann Machines for Classification of Hepatocellular Carcinoma. (14th April 2014)

• Record Type: Journal Article
• Authors: Koziol, James A.; Tan, Eng M.; Dai, Liping; Ren, Pengfei; Zhang, Jian-Ying
• Other Names: Maglietta Rosalia Academic Editor.
• Is Part Of: Computational biology journal. Volume 2014(2014)
• Publication Date: 2014-04-14
• Subjects: Computational biology -- Periodicals; Computational biology; Biología -- Publicaciones periódicas; Ciencias -- Publicaciones periódicas; Periodicals; Electronic journals; 570.285
• DOI: 10.1155/2014/418069
• Languages: English
• ISSNs: 2314-4165

Abstract

Abstract : 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.