Lung cancer cell identification based on artificial neural network ensembles

An artificial neural network ensemble is a learning paradigm where several artificial neural networks are jointly used to solve a problem. In this paper, an automatic pathological diagnosis procedure named Neural Ensemble based Detection (NED) is proposed, which utilizes an artificial neural network ensemble to identify lung cancer cells in the images of the specimens of needle biopsies obtained from the bodies of the subjects to be diagnosed. The ensemble is built on a two-level ensemble architecture. The first-level ensemble is used to judge whether a cell is normal with high confidence where each individual network has only two outputs respectively normal cell or cancer cell. The predictions of those individual networks are combined by a novel method presented in this paper, i.e. full voting which judges a cell to be normal only when all the individual networks judge it is normal. The second-level ensemble is used to deal with the cells that are judged as cancer cells by the first-...

• Type: Journal
• Year: 2002
• Where: ARTMED
• Authors: Zhi-Hua Zhou, Yuan Jiang, Yu-Bin Yang, Shifu Chen
• Keywords: Artificial Neural Network, ARTMED 2002, Cancer Cells, Individual Networks