Background Multiple commercial artificial intelligence (AI) products exist for assessing
radiographs; however, comparable performance data for these algorithms are limited …

Objectives Early identification of lung cancer on chest radiographs improves patient
outcomes. Artificial intelligence (AI) tools may increase diagnostic accuracy and streamline …

Purpose To evaluate the added value of computer-aided detection (CAD) for lung nodules
on chest radiographs when radiologists have bone-suppressed images (BSIs) available …

Objective Radiographic bone age assessment (BAA) is used in the evaluation of pediatric
endocrine and metabolic disorders. We previously developed an automated artificial …

Importance Most early lung cancers present as pulmonary nodules on imaging, but these
can be easily missed on chest radiographs. Objective To assess if a novel artificial …

This study aimed to compare the diagnostic effectiveness of computer-aided detection
(CAD) software (OnGuard™ 5.2) in combination with hardware-based bone suppression …

Background The purpose of this paper is to demonstrate a mechanism for deploying and
validating an AI-based system for detecting abnormalities on chest X-ray scans at the Phu …

Background The autonomous artificial intelligence (AI) system for bone age rating
(BoneXpert) was designed to be used in clinical radiology practice as an AI-replace tool …

RATIONALE AND OBJECTIVES: We sought to assess the performance of a real-time
interactive pulmonary nodule analysis system for evaluation of chest digital radiographic …

Purpose There are few computer-aided detection (CAD) systems that are available for the
detection of nodules on chest radiographs. We evaluated the performance of a Food and …