AIMC Topic: Radiography
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Comparison of state-of-the-art machine and deep learning algorithms to classify proximal humeral fractures using radiology text.
European journal of radiology
May 20, 2022
INTRODUCTION: Proximal humeral fractures account for a significant proportion of all fractures. Detailed accurate classification of the type and severity of the fracture is a key component of clinical decision making, treatment and plays an important...
A pediatric wrist trauma X-ray dataset (GRAZPEDWRI-DX) for machine learning.
Scientific data
May 20, 2022
Digital radiography is widely available and the standard modality in trauma imaging, often enabling to diagnose pediatric wrist fractures. However, image interpretation requires time-consuming specialized training. Due to astonishing progress in comp...
Deep Learning Algorithms Improve the Detection of Subtle Lisfranc Malalignments on Weightbearing Radiographs.
Foot & ankle international
May 19, 2022
BACKGROUND: Detection of Lisfranc malalignment leading to the instability of the joint, particularly in subtle cases, has been a concern for foot and ankle care providers. X-ray radiographs are the mainstay in the diagnosis of these injuries; thus, i...
Prediction of future healthcare expenses of patients from chest radiographs using deep learning: a pilot study.
Scientific reports
May 18, 2022
Our objective was to develop deep learning models with chest radiograph data to predict healthcare costs and classify top-50% spenders. 21,872 frontal chest radiographs were retrospectively collected from 19,524 patients with at least 1-year spending...
Deep learning of birth-related infant clavicle fractures: a potential virtual consultant for fracture dating.
Pediatric radiology
May 17, 2022
BACKGROUND: In infant abuse investigations, dating of skeletal injuries from radiographs is desirable to reach a clear timeline of traumatic events. Prior studies have used infant birth-related clavicle fractures as a surrogate to develop a framework...
The future of radiology: What if artificial intelligence is really as good as predicted?
Diagnostic and interventional imaging
May 13, 2022
Elements of a Good Radiology Artificial Intelligence Paper.
Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
May 10, 2022
Multi-input adaptive neural network for automatic detection of cervical vertebral landmarks on X-rays.
Computers in biology and medicine
May 6, 2022
Cervical vertebral landmark detection is a significant pre-task for vertebral relative motion parameter measurement, which is helpful for doctors to diagnose cervical spine diseases. Accurate cervical vertebral landmark detection could provide reliab...
Translating medical image to radiological report: Adaptive multilevel multi-attention approach.
Computer methods and programs in biomedicine
May 4, 2022
BACKGROUND AND OBJECTIVE: Medical imaging techniques are widely employed in disease diagnosis and treatment. A readily available medical report can be a useful tool in assisting an expert for investigating the patient's health. A radiologist can bene...
Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?
BMC medical research methodology
Apr 28, 2022
BACKGROUND: The health crisis resulting from the global COVID-19 pandemic highlighted more than ever the need for rapid, reliable and safe methods of diagnosis and monitoring of respiratory diseases. To study pulmonary involvement in detail, one of t...
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