OBJECTIVES: To assess the knowledge and perception of artificial intelligence (AI) among radiology residents across Saudi Arabia and assess their interest in learning about AI.
BACKGROUND: Cancer is one of the life-threatening diseases which is affecting a large number of population worldwide. Cancer cells multiply inside the body without showing much symptoms on the surface of the skin, thereby making it difficult to predi...
OBJECTIVE: The aim of this study was to evaluate the effect of a deep learning based computer-aided diagnosis (DL-CAD) system on radiologists' interpretation accuracy and efficiency in reading biparametric prostate magnetic resonance imaging scans.
BACKGROUND: Artificial intelligence (AI) algorithms can be trained to recognise tuberculosis-related abnormalities on chest radiographs. Various AI algorithms are available commercially, yet there is little impartial evidence on how their performance...
Journal of medical imaging and radiation oncology
Aug 1, 2021
INTRODUCTION: The Royal Australian and New Zealand College of Radiologists (RANZCR) led the medical community in Australia and New Zealand in considering the impact of machine learning and artificial intelligence (AI) in health care. RANZCR identifie...
OBJECTIVES: The aim of this study was to leverage volumetric quantification of airspace disease (AD) derived from a superior modality (computed tomography [CT]) serving as ground truth, projected onto digitally reconstructed radiographs (DRRs) to (1)...
OBJECTIVE: Demonstrate the importance of combining multiple readers' opinions, in a context-aware manner, when establishing the reference standard for validation of artificial intelligence (AI) applications for, chest radiographs. By comparing indiv...
The aim of this investigation was to compare the diagnostic performance of radiographers and deep learning algorithms in pulmonary nodule/mass detection on chest radiograph.A test set of 100 chest radiographs containing 53 cases with no pathology (no...
Radiographics : a review publication of the Radiological Society of North America, Inc
Jan 1, 2021
Deep learning is a class of machine learning methods that has been successful in computer vision. Unlike traditional machine learning methods that require hand-engineered feature extraction from input images, deep learning methods learn the image fea...
Journal of X-ray science and technology
Jan 1, 2021
Tuberculosis (TB) is a major health issue with high mortality rates worldwide. Recently, tremendous researches of artificial intelligence (AI) have been conducted targeting at TB to reduce the diagnostic burden. However, most researches are conducted...