With the rapid development in technology, large amounts of high-dimensional data have
been generated. This high dimensionality including redundancy and irrelevancy poses a …

Obtaining informative features is crucial in imbalanced classification. However, existing
neighborhood rough set-based feature selection approaches easily overlook the diversity …

Prostate cancer is one of the most common forms of cancer in men in many countries. The
survival rate can be significantly enhanced with early detection of the cancer so that …

Partial label learning refers to the issue that each training sample corresponds to a
candidate label set containing only one valid label. Feature selection can be viewed as an …

Abstract Machine learning and data mining rely on feature selection to reduce the dimension
of data and increase the performance of algorithms. As a result of such a large search …

An accurate prediction of cardiac disease is a crucial task for medical and research
organizations. Cardiac patients are usually facing heart attacks sometimes tends to death …

Background and objective Integrating multi-omics data for the comprehensive analysis of the
biological processes in human diseases has become one of the most challenging tasks of …

This study develops a clinical decision support system to assist physicians with monitoring
Polycystic Ovarian Syndrome (PCOS). The proposed method uses a classification model …

One of the most important resources used in today's world is image. Medical images can
play an essential role in helping diagnose diseases. Doctors and specialists use medical …

This paper proposes binary versions of artificial rabbits optimization (ARO) for feature
selection (FS) with medical diagnosis data. ARO is a recent swarm-based optimization …