Technologies have driven big data collection across many fields, such as genomics and
business intelligence. This results in a significant increase in variables and data points …

Identifying a small subset of informative genes from a gene expression dataset is an
important process for sample classification in the fields of bioinformatics and machine …

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 design of an optimal framework for the prediction of cancer from high-dimensional and
imbalanced microarray data is a challenging job in the fields of bioinformatics and machine …

Feature Selection (FS) is a major preprocessing stage which aims to improve Machine
Learning (ML) models' performance by choosing salient features, while reducing the …

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' …

For optimal results, retrieving a relevant feature from a microarray dataset has become a hot
topic for researchers involved in the study of feature selection (FS) techniques. The aim of …

Feature selection is critical in analyzing microarray data, which has many features (genes)
or dimensions. However, with only a few samples the large search space and time …

Though several AI-based models have been established for COVID-19 diagnosis, the
machine-based diagnostic gap is still ongoing, making further efforts to combat this epidemic …

India is severely affected by the COVID-19 pandemic and is facing an unprecedented public
health emergency. While the country's immediate measures focus on combating the …