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ARTMED
2002
119views more  ARTMED 2002»
13 years 4 months ago
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...
Zhi-Hua Zhou, Yuan Jiang, Yu-Bin Yang, Shifu Chen
ICMLA
2008
13 years 6 months ago
Tumor Targeting for Lung Cancer Radiotherapy Using Machine Learning Techniques
Accurate lung tumor targeting in real time plays a fundamental role in image-guide radiotherapy of lung cancers. Precise tumor targeting is required for both respiratory gating an...
Tong Lin, Laura Cervino, Xiaoli Tang, Nuno Vasconc...
IJCNN
2008
IEEE
13 years 11 months ago
Dataset complexity can help to generate accurate ensembles of k-nearest neighbors
— Gene expression based cancer classification using classifier ensembles is the main focus of this work. A new ensemble method is proposed that combines predictions of a small ...
Oleg Okun, Giorgio Valentini
BMCBI
2011
12 years 12 months ago
Motif-guided sparse decomposition of gene expression data for regulatory module identification
Background: Genes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for e...
Ting Gong, Jianhua Xuan, Li Chen, Rebecca B. Riggi...
BMCBI
2010
165views more  BMCBI 2010»
13 years 5 months ago
MTar: a computational microRNA target prediction architecture for human transcriptome
Background: MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in importa...
Vinod Chandra, Reshmi Girijadevi, Achuthsankar S. ...