Abstract Machine Learning (ML) and Deep Learning (DL) have achieved high success in
many textual, auditory, medical imaging, and visual recognition patterns. Concerning the …

The healthcare sector, characterized by vast datasets and many diseases, is pivotal in
shaping community health and overall quality of life. Traditional healthcare methods, often …

With the swift pace of the development of artificial intelligence (AI) in diverse spheres, the
medical and healthcare fields are utilizing machine learning (ML) methodologies in …

Nowadays, machine learning (ML) has attained a high level of achievement in many
contexts. Considering the significance of ML in medical and bioinformatics owing to its …

In recent years, the proliferation of deep learning (DL) techniques has given rise to a
significant challenge in the form of deepfake videos, posing a grave threat to the authenticity …

Data classification is the most common task in machine learning, and feature selection is the
key step in the classification task. Common feature selection methods mainly analyze the …

The current investigations provides a stochastic platform using the computational Levenberg-
Marquardt Backpropagation (LMB) neural network (NN) approach, ie, LMB-NN for solving …

In this paper, a new physical layer authenticated encryption (PLAE) scheme based on the
multi-parameter fractional Fourier transform–Orthogonal frequency division multiplexing (MP …

Load balancing problem is important in cloud computing for effectively managing the cloud
resources. It entails distributing incoming network traffic or computational workload among …

This study presents a novel Hunger Game Search and Niching Chimp Optimization
Algorithms (HGS-NChOA) for optimizing grid-connected desalination plants powered by …