The SARS-CoV-2 virus pandemic had devastating effects on various aspects of life: clinical
cases, ranging from mild to severe, can lead to lung failure and to death. Due to the high …

Healthcare delivery during the initial days of outbreak of COVID-19 pandemic was badly
impacted due to large number of severely infected patients posing an unprecedented global …

Background: This paper presents a novel lightweight approach based on machine learning
methods supporting COVID-19 diagnostics based on X-ray images. The presented schema …

Today, deep neural networks are widely used since they can handle a variety of complex
tasks. Their generality makes them very powerful tools in modern technology. However …

Radiomics, an emerging discipline in medical imaging, focuses on extracting detailed
quantitative features from images to unveil subtle patterns imperceptible to the naked eye …

In this paper, we present the major results from the Covid Radiographic imaging System
based on AI (Co. RSA) project, which took place in Italy. This project aims to develop a state …

While deep neural networks are highly effective at solving complex tasks, their
computational demands can hinder their usefulness in real-time applications and with …

Vision transformers (ViT) have been of broad interest in recent theoretical and empirical
works. They are state-of-the-art thanks to their attention-based approach, which boosts the …

In this paper, we present the significant results from the Covid Radiographic imaging System
based on AI (Co. RSA) project, which took place in Italy. This project aims to develop a state …

The main challenges limiting the adoption of deep learning-based solutions in medical
workflows are the availability of annotated data and the lack of interpretability of such …