Background Acute respiratory distress syndrome (ARDS) is a common, but under-
recognised, critical illness syndrome associated with high mortality. An important factor in its …

Acute respiratory distress syndrome (ARDS) is a life-threatening lung injury with global
prevalence and high mortality. Chest x-rays (CXR) are critical in the early diagnosis and …

We aimed to develop a deep learning algorithm detecting 10 common abnormalities (DLAD-
10) on chest radiographs, and to evaluate its impact in diagnostic accuracy, timeliness of …

There is a growing gap between studies describing the capabilities of artificial intelligence
(AI) diagnostic systems using deep learning versus efforts to investigate how or when to …

Background The performance of a deep learning (DL) algorithm should be validated in
actual clinical situations, before its clinical implementation. Purpose To evaluate the …

Early identification of pneumonia is essential in patients with acute febrile respiratory illness
(FRI). We evaluated the performance and added value of a commercial deep learning (DL) …

Artificial intelligence is gaining increasing relevance in the field of radiology. This study
retrospectively evaluates how a commercially available deep learning algorithm can detect …

Background Patients presenting to the emergency department (ED) with acute chest pain
(ACP) syndrome undergo additional testing to exclude acute coronary syndrome (ACS) …

Background There is interest in using convolutional neural networks (CNNs) to analyze
medical imaging to provide computer-aided diagnosis (CAD). Recent work has suggested …

Importance Interpretation of chest radiographs is a challenging task prone to errors,
requiring expert readers. An automated system that can accurately classify chest …