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

Heart disease is recognized as one of the leading factors of death rate worldwide.
Biomedical instruments and various systems in hospitals have massive quantities of clinical …

This review paper delves into synergistic integration of artificial intelligence (AI) and
machine learning (ML) with high-throughput experimentation (HTE) in the field of …

The goal of coreset selection in supervised learning is to produce a weighted subset of data,
so that training only on the subset achieves similar performance as training on the entire …

The high fall rate of the elderly brings enormous challenges to families and the medical
system; therefore, early risk assessment and intervention are quite necessary. Compared to …

Nowadays, the energy sector is experiencing a profound transition. Among all renewable
energy sources, wind energy is the most developed technology across the world. To ensure …

Most existing feature selection methods rank all the features by a certain criterion via which
the top ranking features are selected for the subsequent classification or clustering tasks …

Conventional coronary heart disease (CHD) detection methods are expensive, rely much on
doctors' subjective experience, and some of them have side effects. In order to obtain rapid …

Optimization problems can be seen in numerous fields of practical studies. One area making
waves in the application of optimization methods is data mining in machine learning. An …

Diabetes complications have a significant impact on patients' quality of life. The objective of
this study was to predict which patients were more likely to be in a complicated health …