Gene expression data have become increasingly important in machine learning and
computational biology over the past few years. In the field of gene expression analysis …

In recent decades, the improvement of computer technology has increased the growth of
high-dimensional microarray data. Thus, data mining methods for DNA microarray data …

Background There are similarities and differences between chronic obstructive pulmonary
disease (COPD) and asthma patients in terms of computed tomography (CT) disease …

Background Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease
(ILD) with unknown etiology, characterized by sustained damage repair of epithelial cells …

This study proposes a supervised feature selection technique for classification in high
dimensional binary class problems by adding robustness in the conventional Fisher Score …

Over 400,000 people are estimated to have been exposed to World Trade Center particulate
matter (WTC PM) since the attack on the Twin Towers in Lower Manhattan on September 11 …

Motivation A feature selection algorithm may select the subset of features with the best
associations with the class labels. The recursive feature elimination (RFE) is a heuristic …

In this paper, a novel feature selection method called Robust Proportional Overlapping
Score (RPOS), for microarray gene expression datasets has been proposed, by utilizing the …

The classification of bioimages plays an important role in several biological studies, such as
subcellular localisation, phenotype identification and other types of histopathological …

Background Multi-omics research has the potential to holistically capture intra-tumor
variability, thereby improving therapeutic decisions by incorporating the key principles of …