This systematic review provides researchers interested in feature selection (FS) for
processing microarray data with comprehensive information about the main research …

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

The use of metaheuristics is widespread for optimization in both scientific and industrial
problems due to several reasons, including flexibility, simplicity, and robustness. Grey Wolf …

The data-driven modern era has enabled the collection of large amounts of biomedical and
clinical data. DNA microarray gene expression datasets have mainly gained significant …

Abstract The Sine Cosine Algorithm (SCA) has received much attention from engineering
and scientific fields since it was proposed. Nevertheless, when solving multimodal or …

Medical decision-making with high-dimensional complex data has recently become a focus
and difficulty in artificial intelligence and the medical field. Tumor diagnosis using data …

Feature selection is a process to reduce the dimension of a dataset by removing redundant
features, and to use the optimal subset of features for machine learning or data mining …

Ant colony optimization (ACO) is a well-explored meta-heuristic algorithm, among whose
many applications feature selection (FS) is an important one. Most existing versions of ACO …

The “curse of dimensionality” is one of the largest problems that influences the quality of the
optimization process in most data mining, pattern recognition, and machine learning tasks …

Gene Expression is the process of determining the physical characteristics of living beings
by generating the necessary proteins. Gene Expression takes place in two steps, translation …