Objective This study aimed to investigate the feasibility of using artificial intelligence (AI) to
identify normal chest radiography (CXR) from the worklist of radiologists in a health …

Rationale: Artificial intelligence (AI)–assisted diagnosis imparts high accuracy to chest
radiography (CXR) interpretation; however, its benefit for nonradiologist physicians in …

Objectives To investigate the efficacy of an artificial intelligence (AI) system for the
identification of false negatives in chest radiographs that were interpreted as normal by …

Objectives We aim ed to evaluate a commercial artificial intelligence (AI) solution on a
multicenter cohort of chest radiographs and to compare physicians' ability to detect and …

Objective The clinical impact of artificial intelligence-based computer-aided detection (AI-
CAD) beyond diagnostic accuracy remains uncertain. We aimed to investigate the influence …

1Department of Radiology, Research Institute of Radiological Science and Center for
Clinical Imaging Data Science, Yongin Severance Hospital, Yonsei University College of …

Objectives: To assess the use of artificial intelligence-based software in ruling out chest X-
ray cases, with no significant findings in a primary health care setting. Methods: In this …

Background Chest radiography remains the most common radiologic examination, and
interpretation of its results can be difficult. Purpose To explore the potential benefit of …

Objective It is unknown whether artificial intelligence-based computer-aided detection (AI-
CAD) can enhance the accuracy of chest radiograph (CR) interpretation in real-world clinical …

Objectives Chest radiographs (CXRs) are commonly performed in emergency units (EUs),
but the interpretation requires radiology experience. We developed an artificial intelligence …