With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …

Recent advances in deep learning have led to a promising performance in many medical
image analysis tasks. As the most commonly performed radiological exam, chest …

Abstract Novel coronavirus disease (nCOVID-19) is the most challenging problem for the
world. The disease is caused by severe acute respiratory syndrome coronavirus-2 (SARS …

Background Chest radiograph interpretation is critical for the detection of thoracic diseases,
including tuberculosis and lung cancer, which affect millions of people worldwide each year …

We propose a novel attention gate (AG) model for medical image analysis that automatically
learns to focus on target structures of varying shapes and sizes. Models trained with AGs …

Convolutional neural networks (CNN) are widely used in computer vision and medical
image analysis as the state-of-the-art technique. In CNN, pooling layers are included mainly …

Abstract Vision Transformers (ViTs), with the magnificent potential to unravel the information
contained within images, have evolved as one of the most contemporary and dominant …

Deep reinforcement learning (DRL) augments the reinforcement learning framework, which
learns a sequence of actions that maximizes the expected reward, with the representative …

Recently, we witnessed a tremendous effort to conquer the realm of acoustics as a possible
playground to test with topologically protected sound wave propagation. In this article, we …

Purpose To develop and test an artificial intelligence (AI) system, based on deep
convolutional neural networks (CNNs), for automated real-time triaging of adult chest …