In this review, we address the issue of fairness in the clinical integration of artificial
intelligence (AI) in the medical field. As the clinical adoption of deep learning algorithms, a …

What has happened in machine learning lately, and what does it mean for the future of
medical image analysis? Machine learning has witnessed a tremendous amount of attention …

Accurate air quality forecasting is critical for systematic pollution control as well as public
health and wellness. Most of the traditional forecasting techniques have shown inconsistent …

Background: Recently, Coronavirus Disease 2019 (COVID-19), caused by severe acute
respiratory syndrome virus 2 (SARS-CoV-2), has affected more than 200 countries and lead …

In this study, a novel AI system based on deep learning methods was evaluated to
determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks …

Convolutional neural networks (CNNs) constitute a widely used deep learning approach that
has frequently been applied to the problem of brain tumor diagnosis. Such techniques still …

Purpose Artificial intelligence (AI) is playing an ever-increasing role in Neuroradiology.
Methods When designing AI-based research in neuroradiology and appreciating the …

The accuracy of a predictive system is critical for predictive maintenance and to support the
right decisions at the right times. Statistical models, such as ARIMA and SARIMA, are unable …

Computer-aided medical image analysis plays a significant role in assisting medical
practitioners for expert clinical diagnosis and deciding the optimal treatment plan. At present …

Artificial intelligence (AI) is a branch of computer science that deals with the development of
algorithms that seek to simulate human intelligence. We provide an overview of the basic …