In the era of healthcare and its related research fields, the dimensionality problem of high-
dimensional data is a massive challenge as it is crucial to identify significant genes while …

The detection of nucleic acid marker is essential for accurate and timely diagnosis and
prognosis of different types of diseases. However, the sensitivity and specificity of the assay …

In recent years, medical data analysis has become paramount in delivering accurate
diagnoses for various diseases. The plethora of medical data sources, encompassing …

Feature selection algorithms are frequently employed in preprocessing machine learning
pipelines applied to biological data to identify relevant features. The use of feature selection …

Cancer remains a substantial worldwide health issue that requires careful and exact
classification to plan treatment in its early stages. Classical methods of cancer diagnosis …

The selection of disease-causing genes from gene expression and methylation data is a
great benefit for cancer diagnosis and treatment, but it also faces the limitations due to single …

Dynamic selection techniques select a subset of the classifiers from a pool according to their
perceived competence in labeling each given query instance in particular. To do so, most …

The realms of modern medicine and biology have provided substantial data sets of genetic
roots that exhibit a high dimensionality. Clinical practice and associated processes are …

Gene selection eliminates redundant or duplicate information to optimize computational
resources and improve classification accuracy. In this research, a novel gene selection …

Microarrays have been proven to be beneficial for understanding the genetics of disease.
They are used to assess many different types of cancers. Machine learning algorithms, like …