Background: Three and half million anonymous X-rays were gathered from 45 locations
worldwide (in-hospital and outpatient settings). qXR was initially trained on this massive …

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 …

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

Early detection increases overall survival among patients with lung cancer. This study
formulated a machine learning method that processes chest X-rays (CXRs) to detect lung …

Computer-assisted diagnosis (CAD) algorithms have shown its usefulness for the
identification of pulmonary nodules in chest x-rays, but its capability to diagnose lung cancer …

Lung nodule classification is one of the main topics related to computer‐aided detection
systems. Although convolutional neural networks (CNNs) have been demonstrated to …

Background: Lung cancer has become a major cause of cancer-related deaths. Detection of
potentially malignant lung nodules is essential for the early diagnosis and clinical …

AIM To test the diagnostic performance of a deep learning-based system for the detection of
clinically significant pulmonary nodules/masses on chest radiographs. MATERIALS AND …

Chest X-rays are considered to be the most widely used technique within the health industry
for the detection of lung cancers. Nevertheless, it is very difficult to identify lung nodules …

Background Artificial intelligence (AI) based on deep learning and convolutional neural
networks (CNN) has been applied to various medical fields. We have started to develop …