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Deep Learning for Diagnosis and Segmentation of Pneumothorax: The Results on the Kaggle Competition and Validation Against Radiologists.

IEEE journal of biomedical and health informatics
Pneumothorax is potentially a life-threatening disease that requires urgent diagnosis and treatment. The chest X-ray is the diagnostic modality of choice when pneumothorax is suspected. The computer-aided diagnosis of pneumothorax has received a dram...

Radiologists versus Deep Convolutional Neural Networks: A Comparative Study for Diagnosing COVID-19.

Computational and mathematical methods in medicine
The reverse transcriptase polymerase chain reaction (RT-PCR) is still the routinely used test for the diagnosis of SARS-CoV-2 (COVID-19). However, according to several reports, RT-PCR showed a low sensitivity and multiple tests may be required to rul...

ai-corona: Radiologist-assistant deep learning framework for COVID-19 diagnosis in chest CT scans.

PloS one
The development of medical assisting tools based on artificial intelligence advances is essential in the global fight against COVID-19 outbreak and the future of medical systems. In this study, we introduce ai-corona, a radiologist-assistant deep lea...

Generative Adversarial Networks: A Primer for Radiologists.

Radiographics : a review publication of the Radiological Society of North America, Inc
Artificial intelligence techniques involving the use of artificial neural networks-that is, deep learning techniques-are expected to have a major effect on radiology. Some of the most exciting applications of deep learning in radiology make use of ge...

2020 ACR Data Science Institute Artificial Intelligence Survey.

Journal of the American College of Radiology : JACR
PURPOSE: The ACR Data Science Institute conducted its first annual survey of ACR members to understand how radiologists are using artificial intelligence (AI) in clinical practice and to provide a baseline for monitoring trends in AI use over time.

Radiologists in the loop: the roles of radiologists in the development of AI applications.

European radiology
OBJECTIVES: To examine the various roles of radiologists in different steps of developing artificial intelligence (AI) applications.

Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage.

Neuroradiology
PURPOSE: To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT angiography (CTA) in aneurysmal subarachnoid hemorrhage (aSAH).

Clinical applications of AI in MSK imaging: a liability perspective.

Skeletal radiology
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...