AIMC Topic: Radiography
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Chest x-ray automated triage: A semiologic approach designed for clinical implementation, exploiting different types of labels through a combination of four Deep Learning architectures.
Computer methods and programs in biomedicine
May 2, 2021
BACKGROUND AND OBJECTIVES: The multiple chest x-ray datasets released in the last years have ground-truth labels intended for different computer vision tasks, suggesting that performance in automated chest x-ray interpretation might improve by using ...
Progressive Transmission of Medical Images via a Bank of Generative Adversarial Networks.
Journal of healthcare engineering
Apr 28, 2021
The healthcare sector is currently undergoing a major transformation due to the recent advances in deep learning and artificial intelligence. Despite a significant breakthrough in medical imaging and diagnosis, there are still many open issues and un...
A calibrated deep learning ensemble for abnormality detection in musculoskeletal radiographs.
Scientific reports
Apr 27, 2021
Musculoskeletal disorders affect the locomotor system and are the leading contributor to disability worldwide. Patients suffer chronic pain and limitations in mobility, dexterity, and functional ability. Musculoskeletal (bone) X-ray is an essential t...
Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation.
The Lancet. Digital health
Apr 20, 2021
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common, but under-recognised, critical illness syndrome associated with high mortality. An important factor in its under-recognition is the variability in chest radiograph interpretation for...
Middle Aged
Lung
Deep Learning
United States
Hospitals
Aged
Male
Retrospective Studies
Female
Humans
Radiography, Thoracic
Neural Networks, Computer
Pleural Cavity
Algorithms
Radiography
Pleural Diseases
Respiratory Distress Syndrome
Radiographic Image Interpretation, Computer-Assisted
Area Under Curve
Datasets as Topic
Radiologists in the loop: the roles of radiologists in the development of AI applications.
European radiology
Apr 16, 2021
OBJECTIVES: To examine the various roles of radiologists in different steps of developing artificial intelligence (AI) applications.
Artificial intelligence in radiology: 100 commercially available products and their scientific evidence.
European radiology
Apr 15, 2021
OBJECTIVES: Map the current landscape of commercially available artificial intelligence (AI) software for radiology and review the availability of their scientific evidence.
Machine learning solutions in radiology: does the emperor have no clothes?
European radiology
Apr 15, 2021
• Interest in radiomics and machine learning is steadily increasing and is reflected both in research output and number of commercially available solutions.• Currently available commercial products using machine learning are often supported by limite...
Artificial intelligence development in pediatric body magnetic resonance imaging: best ideas to adapt from adults.
Pediatric radiology
Apr 13, 2021
Emerging manifestations of artificial intelligence (AI) have featured prominently in virtually all industries and facets of our lives. Within the radiology literature, AI has shown great promise in improving and augmenting radiologist workflow. In pe...
Clinical applications of AI in MSK imaging: a liability perspective.
Skeletal radiology
Apr 9, 2021
Artificial intelligence (AI) applications have been gaining traction across the radiology space, promising to redefine its workflow and delivery. However, they enter into an uncertain legal environment. This piece examines the nature, exposure, and t...
Deep learning for detection of radiographic sacroiliitis: achieving expert-level performance.
Arthritis research & therapy
Apr 8, 2021
BACKGROUND: Radiographs of the sacroiliac joints are commonly used for the diagnosis and classification of axial spondyloarthritis. The aim of this study was to develop and validate an artificial neural network for the detection of definite radiograp...
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