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 …

In smart cities, ensuring road safety and optimizing transportation efficiency heavily relies on
streamlined road condition monitoring. The application of Artificial Intelligence (AI) has …

Purpose Monitoring corporate credit risk (CCR) has traditionally relied on such indicators as
income, debt and inventory at a company level. These data are usually released on a …

This review article delves into applying deep learning methodologies in conjunction with
microarray data for cancer classification. The study provides a comprehensive overview of …

Cancer is a group of diseases leads to higher mortality rate due to abnormal growth of cell
within body tissues. Microarray dataset incorporates features those are challenge due to …

Feature selection in high dimensional gene expression datasets not only reduces the
dimension of the data, but also the execution time and computational cost of the underlying …

The brain is the most vital organ present in the human body & no doubt that if abnormal
growth of brain cells has been detected, it leads to the development of Brain Tumor (BT) …

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 …

Computer-aided decision support systems (DSSs) are becoming popular in a variety of
professions. Notably, medical DSSs assist healthcare professionals (decision makers) …