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Radiology

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Can AI outperform a junior resident? Comparison of deep neural network to first-year radiology residents for identification of pneumothorax.

Emergency radiology
PURPOSE: To (1) develop a deep learning system (DLS) using a deep convolutional neural network (DCNN) for identification of pneumothorax, (2) compare its performance to first-year radiology residents, and (3) evaluate the ability of a DLS to augment ...

The first use of artificial intelligence (AI) in the ER: triage not diagnosis.

Emergency radiology
Predictions related to the impact of AI on radiology as a profession run the gamut from AI putting radiologists out of business to having no effect at all. The use of AI appears to show significant promise in ER triage in the present. We briefly disc...

2020 ACR Presidential Address: Quality, Ownership, and Our Role as Physicians.

Journal of the American College of Radiology : JACR
A story from long ago reminds us of the importance of quality in our practices, of taking ownership of our patients, and of our role as physicians. The coronavirus disease 2019 (COVID-19) pandemic has disrupted our practices. Before the pandemic, man...

Medical Student Perspectives on the Impact of Artificial Intelligence on the Practice of Medicine.

Current problems in diagnostic radiology
INTRODUCTION: Concerns about radiologists being replaced by artificial intelligence (AI) from the lay media could have a negative impact on medical students' perceptions of radiology as a viable specialty. The purpose of this study was to evaluate Un...

Understanding spatial language in radiology: Representation framework, annotation, and spatial relation extraction from chest X-ray reports using deep learning.

Journal of biomedical informatics
Radiology reports contain a radiologist's interpretations of images, and these images frequently describe spatial relations. Important radiographic findings are mostly described in reference to an anatomical location through spatial prepositions. Suc...

Artificial intelligence from A to Z: From neural network to legal framework.

European journal of radiology
Artificial intelligence (AI) will continue to cause substantial changes within the field of radiology, and it will become increasingly important for clinicians to be familiar with several concepts behind AI algorithms in order to effectively guide th...

Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors.

European radiology
OBJECTIVE: The objective was to identify barriers and facilitators to the implementation of artificial intelligence (AI) applications in clinical radiology in The Netherlands.

Deep learning for dermatologists: Part II. Current applications.

Journal of the American Academy of Dermatology
Because of a convergence of the availability of large data sets, graphics-specific computer hardware, and important theoretical advancements, artificial intelligence has recently contributed to dramatic progress in medicine. One type of artificial in...