Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Our work concerns the elucidation of the cancer (epi)genome, transcriptome and proteome to better understand the complex interplay between a cancer cell's molecular state and ...
Matthew Holford, James P. McCusker, Kei-Hoi Cheung...
In this paper, we use a level set based segmentation algorithm to extract the vascular tree from Magnetic Resonance Angiography, "MRA". Classification model finds an opt...
Background: Analyzing differential-gene-expression data in the context of protein-interaction networks (PINs) yields information on the functional cellular status. PINs can be for...
Alexander Platzer, Paul Perco, Arno Lukas, Bernd M...
This paper presents a novel hybrid method combining genetic programming and decision tree learning. The method starts by estimating a benchmark level of reasonable accuracy, based ...