AIMC Topic: Radiology

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The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review.

Dento maxillo facial radiology
OBJECTIVES: To investigate the current clinical applications and diagnostic performance of artificial intelligence (AI) in dental and maxillofacial radiology (DMFR).

Current applications and future directions of deep learning in musculoskeletal radiology.

Skeletal radiology
Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of artificial intelligence that is ideally suited to solving image-based problems. There are an increasing number of musculoskeletal applications of deep learning, w...

Artificial intelligence for precision education in radiology.

The British journal of radiology
In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of learning without explicit instruction and has emerging applications in medicine, particularly rad...

Bending the Artificial Intelligence Curve for Radiology: Informatics Tools From ACR and RSNA.

Journal of the American College of Radiology : JACR
Artificial intelligence (AI) will reshape radiology over the coming years. The radiology community has a strong history of embracing new technology for positive change, and AI is no exception. As with any new technology, rapid, successful implementat...

Justifying diagnosis decisions by deep neural networks.

Journal of biomedical informatics
An integrated approach is proposed across visual and textual data to both determine and justify a medical diagnosis by a neural network. As deep learning techniques improve, interest grows to apply them in medical applications. To enable a transition...

Imaging Quality Control in the Era of Artificial Intelligence.

Journal of the American College of Radiology : JACR
The advent of artificial intelligence (AI) promises to have a transformational impact on quality in medicine, including in radiology. However, experience has shown that quality tools alone are often not sufficient to bring about consistent excellent ...

Deep-Learning Language-Modeling Approach for Automated, Personalized, and Iterative Radiology-Pathology Correlation.

Journal of the American College of Radiology : JACR
PURPOSE: Radiology-pathology correlation has long been foundational to continuing education, peer learning, quality assurance, and multidisciplinary patient care. The objective of this study was to determine whether modern deep-learning language-mode...