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

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) …

The recent development of imaging and sequencing technologies enables systematic
advances in the clinical study of lung cancer. Meanwhile, the human mind is limited in …

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 …

Cancer prediction in the early stage is a topic of major interest in medicine since it allows
accurate and efficient actions for successful medical treatments of cancer. Mostly cancer …

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

Gene expression data hide vital information required to understand the biological process
that takes place in a particular organism in relation to its environment. Deciphering the …