Accurate and timely detection and classification of lung abnormalities are crucial for effective
diagnosis and treatment planning. In recent years, Deep Learning (DL) techniques have …

Since the onset of the COVID-19 pandemic in 2019, there has been a concerted effort to
develop cost-effective, non-invasive, and rapid AI-based tools. These tools were intended to …

Significant advancements in machine learning algorithms have the potential to aid in the
early detection and prevention of cancer, a devastating disease. However, traditional …

This study systematically reviews CNN-based medical image classification methods. We
surveyed 149 of the latest and most important papers published to date and conducted an in …

In light of the ongoing battle against COVID-19, while the pandemic may eventually subside,
sporadic cases may still emerge, underscoring the need for accurate detection from …

Background AI for medical diagnosis has made a tremendous impact by applying
convolutional neural networks (CNNs) to medical image classification and momentum plays …

The identification and characterization of lung diseases is one of the most interesting
research topics in recent years. They require accurate and rapid diagnosis. Although lung …

The quick and precise identification of COVID-19 pneumonia, non-COVID-19 viral
pneumonia, bacterial pneumonia, mycoplasma pneumonia, and normal lung on chest CT …

This study presents a novel privacy-preserving self-supervised (SSL) framework for COVID-
19 classification from lung CT scans, utilizing federated learning (FL) enhanced with Paillier …

The digitization of healthcare data has presented a pressing need to address privacy
concerns within the realm of machine learning for healthcare institutions. One promising …