Microarray data plays a major role in diagnosing and treating cancer. In several microarray
data sets, many gene fragments are not associated with the target diseases. A solution to the …

Cancer can be considered as one of the leading causes of death widely. One of the most
effective tools to be able to handle cancer diagnosis, prognosis, and treatment is by using …

The paper addresses the limitations of the Moth-Flame Optimization (MFO) algorithm, a meta-
heuristic used to solve optimization problems. The MFO algorithm, which employs moths' …

Feature selection is an NP-hard combinatorial problem, in which the number of possible
feature subsets increases exponentially with the number of features. In the case of large …

In contemporary research, high-dimensional data has become more popular in many
scientific fields with the rapid advancement of technology in collecting and storing large …

Ensemble feature selection (EFS) is a valuable technique for developing accurate and
robust machine‐learning (ML) models. Data variation plays a crucial role in the success of …

The particle swarm optimization (PSO) algorithm was applied to penalize the Cox model for
predicting long-term outcomes in breast cancer patients. This study utilized data from 198 …

Recent studies have shown that ensemble feature selection (EFS) has achieved outstanding
performance in microarray data classification. However, some issues remain partially …

Microarray technology provides an enormous opportunity to measure large-scale gene
expressions simultaneously. However sparse and high-dimensional feature space posed …

Cancer can be considered as one of the leading causes of death widely. One of the most
effective tools to be able to handle cancer diagnosis, prognosis, and treatment is by using …