Objective The coronavirus disease 2019 pandemic has inspired new innovations in
diagnosing, treating, and dispositioning patients during high census conditions with …

Purpose To investigate the diagnostic performance of an Artificial Intelligence (AI) system for
detection of COVID-19 in chest radiographs (CXR), and compare results to those of …

Background There are characteristic findings of coronavirus disease 2019 (COVID-19) on
chest images. An artificial intelligence (AI) algorithm to detect COVID-19 on chest …

Common lung diseases are first diagnosed using chest X-rays. Here, we show that a fully
automated deep-learning pipeline for the standardization of chest X-ray images, for the …

Background: Considering the large number of patients with pulmonary symptoms admitted
to the emergency department daily, it is essential to diagnose them correctly. It is necessary …

The recent medical applications of deep-learning (DL) algorithms have demonstrated their
clinical efficacy in improving speed and accuracy of image interpretation. If the DL algorithm …

Background Airspace disease as seen on chest X-rays is an important point in triage for
patients initially presenting to the emergency department with suspected COVID-19 …

(1) Background: Chest radiographs are the mainstay of initial radiological investigation in
this COVID-19 pandemic. A reliable and readily deployable artificial intelligence (AI) …

Context: As the burden of COVID-19 enhances, the need of a fast and reliable screening
method is imperative. Chest radiographs plays a pivotal role in rapidly triaging the patients …

Purpose To conduct a prospective observational study across 12 US hospitals to evaluate
real-time performance of an interpretable artificial intelligence (AI) model to detect COVID-19 …