Purpose The detection of pleural effusion in chest radiography is crucial for doctors to make
timely treatment decisions for patients with chronic obstructive pulmonary disease. We used …

Background Supine chest radiography for bedridden patients in intensive care units (ICUs)
is one of the most frequently ordered imaging studies worldwide. Purpose To evaluate the …

Purpose Acute respiratory distress syndrome (ARDS) is a life-threatening condition that can
cause a dramatic drop in blood oxygen levels due to widespread lung inflammation. Chest …

Despite the potential of deep convolutional neural networks for classification of thorax
diseases from chest X-ray images, this task is still challenging as it is categorized as a …

Lung disease is a major health problem due to air pollution, smoking, and an aging
population. For this reason, early and accurate detection is essential to achieve overall …

Featured Application This method based on deep learning may be useful in the computer-
aided detection of multiple lesions on chest X-ray images. Abstract Automated detection of …

Abstract Background and Objectives Chest X-rays are the most commonly performed,
costeffective diagnostic imaging tests ordered by physicians. A clinically validated …

A major obstacle to the integration of deep learning models for chest x-ray interpretation into
clinical settings is the lack of understanding of their failure modes. In this work, we first …

Misdiagnosis of pulmonary pathology may have several causes. Some of them are related to
the unavailability of radiology specialists, the increasingly overwhelming number of Chest X …

Background: Chest X-rays are the most commonly performed, cost-effective diagnostic
imaging tests ordered by physicians. A clinically validated AI system that can reliably …