The identification of cancer classes has traditionally been based on histomorphology. Recently, DNA microarrays have been used successfully to automatically discover cancer classes through clustering ...

Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

The advent of gene chips has led to a promising technology for cell, tumor, and cancer classification. We exploit and expand the methodology of recursive partitioning trees for tumor and cell ...

The author investigates how probabilistic classification can be used to enhance credit-scoring accuracy, offering a robust means for assessing model performance ...