This research explores the use of machine learning to predict the mechanical properties of
cementitious materials enhanced with carbon nanotubes (CNTs). Specifically, the study …

In develo** countries, the interaction between rapid urban expansion and population
growth brings forth a host of challenges, particularly concerning essential services like …

At present, there is a pressing need for data scientists and academic researchers to devise
advanced machine learning and artificial intelligence-driven systems that can effectively …

Depression has become a widespread health concern today. Understanding the influencing
factors can promote human mental health as well as provide a basis for exploring preventive …

Abstract Background The Coronavirus Disease 2019 (COVID-19) pandemic was a huge
shock to society, and the ensuing information problems had a huge impact on society at the …

Background Clinical decision support systems based on machine learning (ML) models are
emerging within psychiatry. To ensure their successful implementation, healthcare staff …

The interest of advertising designers and operators in crafting appealing images is steadily
increasing. With a primary focus on image attractiveness, this study endeavors to uncover …

Purpose Women with breast cancer face a high degree of uncertainty. Trust between health
providers and patients has been shown to improve patient quality of life and may enhance …

Federated Learning is a decentralized machine learning method that allows collaborative
model training across several devices or institutions while maintaining the privacy and …

With the widespread use of machine learning for algorithmic decision-making, Explainable
Artificial Intelligence (XAI) systems are increasingly important. However, they are not always …