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Parallel Implementation of Efficient Search Schemes for the Inference of Cancer Progression Models
The emergence and development of cancer is a consequence of the accumulation over time of genomic mutations involving a specific set of genes, which provides the cancer clones with a functional selective advantage.
Investigating the performance of multi-objective optimization when learning Bayesian Networks
Bayesian Networks have been widely used in the last decades in many fields, to describe statistical dependencies among random variables.
USE-Net: incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets
The following mixed scheme is used for training/testing: (i) training on either each individual dataset or multiple prostate MRI datasets and (ii) testing on all three datasets with all possible training/testing combinations.
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