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Radiology

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Qualifying Certainty in Radiology Reports through Deep Learning-Based Natural Language Processing.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Communication gaps exist between radiologists and referring physicians in conveying diagnostic certainty. We aimed to explore deep learning-based bidirectional contextual language models for automatically assessing diagnostic ...

Professionals' responses to the introduction of AI innovations in radiology and their implications for future adoption: a qualitative study.

BMC health services research
BACKGROUND: Artificial Intelligence (AI) innovations in radiology offer a potential solution to the increasing demand for imaging tests and the ongoing workforce crisis. Crucial to their adoption is the involvement of different professional groups, n...

Bag-of-Words Technique in Natural Language Processing: A Primer for Radiologists.

Radiographics : a review publication of the Radiological Society of North America, Inc
Natural language processing (NLP) is a methodology designed to extract concepts and meaning from human-generated unstructured (free-form) text. It is intended to be implemented by using computer algorithms so that it can be run on a corpus of documen...

Assessment of MRI technologists in acceptance and willingness to integrate artificial intelligence into practice.

Radiography (London, England : 1995)
INTRODUCTION: The integration of AI in medical imaging has tremendous exponential growth, especially in image production, image processing and image interpretation. It is expected that radiographers working across all imaging modalities have adequate...

A Conference-Friendly, Hands-on Introduction to Deep Learning for Radiology Trainees.

Journal of digital imaging
Artificial or augmented intelligence, machine learning, and deep learning will be an increasingly important part of clinical practice for the next generation of radiologists. It is therefore critical that radiology residents develop a practical under...

AI MSK clinical applications: spine imaging.

Skeletal radiology
Recent investigations have focused on the clinical application of artificial intelligence (AI) for tasks specifically addressing the musculoskeletal imaging routine. Several AI applications have been dedicated to optimizing the radiology value chain ...

Explicability of artificial intelligence in radiology: Is a fifth bioethical principle conceptually necessary?

Bioethics
Recent years have witnessed intensive efforts to specify which requirements ethical artificial intelligence (AI) must meet. General guidelines for ethical AI consider a varying number of principles important. A frequent novel element in these guideli...

Development and web deployment of an automated neuroradiology MRI protocoling tool with natural language processing.

BMC medical informatics and decision making
BACKGROUND: A systematic approach to MRI protocol assignment is essential for the efficient delivery of safe patient care. Advances in natural language processing (NLP) allow for the development of accurate automated protocol assignment. We aim to de...

Understanding artificial intelligence based radiology studies: CNN architecture.

Clinical imaging
Artificial intelligence (AI) in radiology has gained wide interest due to the development of neural network architectures with high performance in computer vision related tasks. As AI based software programs become more integrated into the clinical w...