AIMC Topic: Radiography
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Automated detection & classification of knee arthroplasty using deep learning.
The Knee
Dec 26, 2019
BACKGROUND: Preoperative identification of knee arthroplasty is important for planning revision surgery. However, up to 10% of implants are not identified prior to surgery. The purposes of this study were to develop and test the performance of a deep...
Artificial intelligence in medical imaging.
Magnetic resonance imaging
Dec 16, 2019
The medical specialty radiology has experienced a number of extremely important and influential technical developments in the past that have affected how medical imaging is deployed. Artificial intelligence (AI) is potentially another such developmen...
Artificial intelligence in diagnostic imaging: impact on the radiography profession.
The British journal of radiology
Dec 16, 2019
The arrival of artificially intelligent systems into the domain of medical imaging has focused attention and sparked much debate on the role and responsibilities of the radiologist. However, discussion about the impact of such technology on the radio...
Identifying bladder rupture following traumatic pelvic fracture: A machine learning approach.
Injury
Dec 9, 2019
INTRODUCTION: Bladder rupture following blunt pelvic trauma is rare though can have significant sequelae. We sought to determine whether machine learning could help predict the presence of bladder injury using certain factors at the time of presentat...
Diagnostic and Gradation Model of Osteoporosis Based on Improved Deep U-Net Network.
Journal of medical systems
Dec 7, 2019
The measurement of bone mineral density for osteoporosis has always been the focus of researchers because it plays an important role in bone disease diagnosis. However, because of X-ray image noise and the large difference between the bone shapes of ...
Integrating Artificial Intelligence Into Radiologic Practice: A Look to the Future.
Journal of the American College of Radiology : JACR
Nov 30, 2019
Meeting of the Minds: Considering the Real Impact of Artificial Intelligence.
Journal of medical imaging and radiation sciences
Nov 26, 2019
The exploration of feature extraction and machine learning for predicting bone density from simple spine X-ray images in a Korean population.
Skeletal radiology
Nov 23, 2019
OBJECTIVE: Osteoporosis is hard to detect before it manifests symptoms and complications. In this study, we evaluated machine learning models for identifying individuals with abnormal bone mineral density (BMD) through an analysis of spine X-ray feat...
Deep learning-based detection system for multiclass lesions on chest radiographs: comparison with observer readings.
European radiology
Nov 20, 2019
OBJECTIVE: To investigate the feasibility of a deep learning-based detection (DLD) system for multiclass lesions on chest radiograph, in comparison with observers.
Artificial Intelligence, Radiology, and Tuberculosis: A Review.
Academic radiology
Nov 20, 2019
Tuberculosis is a leading cause of death from infectious disease worldwide, and is an epidemic in many developing nations. Countries where the disease is common also tend to have poor access to medical care, including diagnostic tests. Recent advance...
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