Support vector machines (SVMs) are well-known machine learning algorithms for
classification and regression applications. In the healthcare domain, they have been used …

Due to market deregulation and globalisation, competitive environments in various sectors
continuously evolve, leading to increased customer churn. Effectively anticipating and …

The investigation compares the conventional, advanced machine, deep, and hybrid learning
models to introduce an optimum computational model to assess the ground vibrations …

The research paper delves into the transformative role of artificial intelligence (AI) in
revolutionizing cybersecurity. This study examines the historical context and evolution of AI …

Cardiovascular disease (CVD) is a life‐threatening disease rising considerably in the world.
Early detection and prediction of CVD as well as other heart diseases might protect many …

Biochar is emerging as a potential solution for biomass conversion to meet the ever
increasing demand for sustainable energy. Efficient management systems are needed in …

Saturated hydraulic conductivity (Ks) is an important soil characteristic that controls water
moves through the soil. On the other hand, its measurement is difficult, time-consuming, and …

Machine learning (ML) algorithms play a vital role in the brain age estimation frameworks.
The impact of regression algorithms on prediction accuracy in the brain age estimation …

Alzheimer's disease (AD) is the most pervasive form of dementia, resulting in severe
psychosocial effects such as affecting personality, reasoning, emotions, and memory …

Loss function plays a vital role in supervised learning frameworks. The selection of the
appropriate loss function holds the potential to have a substantial impact on the proficiency …