Computer-Aided Diagnosis (CAD) systems for chest radiographs using artificial intelligence
(AI) have recently shown a great potential as a second opinion for radiologists. The …

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: Chest X-rays are the most commonly performed, cost-effective diagnostic
imaging tests ordered by physicians. A clinically validated AI system that can reliably …

Purpose: Artificial intelligence (AI) solutions for medical diagnosis require thorough
evaluation to demonstrate that performance is maintained for all patient sub-groups and to …

Interpretation of chest radiographs (CXR) is a difficult but essential task for detecting thoracic
abnormalities. Recent artificial intelligence (AI) algorithms have achieved radiologist-level …

In medical practice, chest X-rays are the most ubiquitous diagnostic imaging tests. However,
the current workload in extensive health care facilities and lack of well-trained radiologists is …

Background Artificial intelligence (AI) systems for automated chest x-ray interpretation hold
promise for standardising reporting and reducing delays in health systems with shortages of …

Aim: This study aimed to develop a reliable multi-classification artificial intelligence (AI) tool
to 79 improve the accuracy and efficiency of chest radiograph diagnosis. 80 Methods: We …

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

Background: The chest radiograph (CXR) is the most frequently performed radiological
examination worldwide. The increasing volume of CXRs performed in hospitals causes …