Recently, feature selection and dimensionality reduction have become fundamental tools for
many data mining tasks, especially for processing high-dimensional data such as gene …

Microarray data classification is a difficult challenge for machine learning researchers due to
its high number of features and the small sample sizes. Feature selection has been soon …

Feature selection is playing an increasingly significant role with respect to many computer
vision applications spanning from object recognition to visual object tracking. However, most …

Filter-based feature selection has become crucial in many classification settings, especially
object recognition, recently faced with feature learning strategies that originate thousands of …

Disease diagnosis and prediction methods in biotechnology and medicine have significantly
advanced over time. Consequently, analyzing raw gene expression is crucial for identifying …

We propose a filtering feature selection framework that considers subsets of features as
paths in a graph, where a node is a feature and an edge indicates pairwise (customizable) …

This paper presents an overview of the image analysis techniques in the domain of
histopathology, specifically, for the objective of automated carcinoma detection and …

Background: We examined plasma microRNA (miRNA) concentrations from patients with
gastric cancers (GCs) to assess their clinical application for diagnosing and monitoring …

Malignant mesothelioma is an aggressive tumor of serosal surfaces, such as the pleura and
the peritoneum. This tumor was once rare, but its incidence is increasing worldwide …

Gene expression microarray classification is a crucial research field as it has been
employed in cancer prediction and diagnosis systems. Gene expression data are composed …