AIMC Topic: Radiography

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Deep learning for accurately recognizing common causes of shoulder pain on radiographs.

Skeletal radiology Feb 20, 2021
OBJECTIVE: Training a convolutional neural network (CNN) to detect the most common causes of shoulder pain on plain radiographs and to assess its potential value in serving as an assistive device to physicians.
Area Under Curve Humans Radiography Neural Networks, Computer Shoulder Pain Retrospective Studies Deep Learning ROC Curve
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The integration of artificial intelligence in medical imaging practice: Perspectives of African radiographers.

Radiography (London, England : 1995) Feb 20, 2021
INTRODUCTION: The current technological developments in medical imaging are centred largely on the increasing integration of artificial intelligence (AI) into all equipment modalities. This survey assessed the perspectives of African radiographers on...
Humans Artificial Intelligence Cross-Sectional Studies Allied Health Personnel Radiography Radiology Department, Hospital
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A Deep Learning Tool for Automated Radiographic Measurement of Acetabular Component Inclination and Version After Total Hip Arthroplasty.

The Journal of arthroplasty Feb 16, 2021
BACKGROUND: Inappropriate acetabular component angular position is believed to increase the risk of hip dislocation after total hip arthroplasty. However, manual measurement of these angles is time consuming and prone to interobserver variability. Th...
Arthroplasty, Replacement, Hip Humans Hip Prosthesis Deep Learning Acetabulum Radiography
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Training opportunities of artificial intelligence (AI) in radiology: a systematic review.

European radiology Feb 15, 2021
OBJECTIVES: The aim is to offer an overview of the existing training programs and critically examine them and suggest avenues for further development of AI training programs for radiologists.
Humans Artificial Intelligence Forecasting Radiography Radiology Radiologists
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Radiographers' perspectives on the emerging integration of artificial intelligence into diagnostic imaging: The Ghana study.

Journal of medical radiation sciences Feb 14, 2021
INTRODUCTION: The integration of artificial intelligence (AI) systems into medical imaging is advancing the practice and patient care. It is thought to further revolutionise the entire field in the near future. This study explored Ghanaian radiograph...
Radiography Ghana Artificial Intelligence Cross-Sectional Studies Humans Allied Health Personnel
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Performance of an artificial intelligence system for bone age assessment in Tibet.

The British journal of radiology Feb 9, 2021
OBJECTIVE: To investigate whether bone age (BA) of children living in Tibet Highland could be accurately assessed using a fully automated artificial intelligence (AI) system.
Radiography Hand Tibet Age Determination by Skeleton Child, Preschool Child Image Processing, Computer-Assisted Male Adolescent Humans Artificial Intelligence Female Reproducibility of Results
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Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study.

Sleep & breathing = Schlaf & Atmung Feb 8, 2021
PURPOSE: In 2-dimensional lateral cephalometric radiographs, patients with severe obstructive sleep apnea (OSA) exhibit a more crowded oropharynx in comparison with non-OSA. We tested the hypothesis that machine learning, an application of artificial...
Sensitivity and Specificity Male Middle Aged Female Adult Sleep Apnea, Obstructive Deep Learning Radiography Cephalometry Humans
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Unsupervised Deep Anomaly Detection in Chest Radiographs.

Journal of digital imaging Feb 8, 2021
The purposes of this study are to propose an unsupervised anomaly detection method based on a deep neural network (DNN) model, which requires only normal images for training, and to evaluate its performance with a large chest radiograph dataset. We u...
Humans Neural Networks, Computer Radiologists Radiography, Thoracic Female Middle Aged Male ROC Curve Radiography
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Differential diagnosis of ameloblastoma and odontogenic keratocyst by machine learning of panoramic radiographs.

International journal of computer assisted radiology and surgery Feb 6, 2021
PURPOSE: The differentiation of the ameloblastoma and odontogenic keratocyst directly affects the formulation of surgical plans, while the results of differential diagnosis by imaging alone are not satisfactory. This paper aimed to propose an algorit...
Sensitivity and Specificity China Diagnosis, Differential Algorithms Reproducibility of Results Rotation Odontogenic Cysts Ameloblastoma Radiography Radiography, Panoramic Radiologists Humans Neural Networks, Computer Machine Learning
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Deep learning for the radiographic diagnosis of proximal femur fractures: Limitations and programming issues.

Orthopaedics & traumatology, surgery & research : OTSR Jan 30, 2021
INTRODUCTION: Radiology is one of the domains where artificial intelligence (AI) yields encouraging results, with diagnostic accuracy that approaches that of experienced radiologists and physicians. Diagnostic errors in traumatology are rare but can ...
Femur Prospective Studies Humans Deep Learning Artificial Intelligence Radiography
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