Applications of machine learning (ML) methods have been used extensively to solve various
complex challenges in recent years in various application areas, such as medical, financial …

Artificial intelligence (AI) is gradually changing medical practice. With recent progress in
digitized data acquisition, machine learning and computing infrastructure, AI applications …

Feature selection techniques have become an apparent need in many bioinformatics
applications. In addition to the large pool of techniques that have already been developed in …

The field of machine learning (ML) is sufficiently young that it is still expanding at an
accelerating pace, lying at the crossroads of computer science and statistics, and at the core …

We summarise various ways of performing dimensionality reduction on high‐dimensional
microarray data. Many different feature selection and feature extraction methods exist and …

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 …

Using automated computer tools and in particular machine learning to facilitate and
enhance medical analysis and diagnosis is a promising and important area. In this paper …

This article reviews machine learning methods for bioinformatics. It presents modelling
methods, such as supervised classification, clustering and probabilistic graphical models for …

A plenitude of feature selection (FS) methods is available in the literature, most of them
rising as a need to analyze data of very high dimension, usually hundreds or thousands of …

Machine learning is one of the most exciting recent technologies in Artificial Intelligence.
Learning algorithms in many applications that's we make use of daily. Every time a web …