AI Medical Compendium Topic:
Radiology

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Clinical Impact of Deep Learning Reconstruction in MRI.

Radiographics : a review publication of the Radiological Society of North America, Inc
Deep learning has been recognized as a paradigm-shifting tool in radiology. Deep learning reconstruction (DLR) has recently emerged as a technology used in the image reconstruction process of MRI, which is an essential procedure in generating MR imag...

Client-Side Application of Deep Learning Models Through Teleradiology.

Studies in health technology and informatics
Deep learning models for radiology are typically deployed either through cloud-based platforms, through on-premises infrastructures, or though heavyweight viewers. This tends to restrict the audience of deep learning models to radiologists working in...

Addressing the Challenges of Implementing Artificial Intelligence Tools in Clinical Practice: Principles From Experience.

Journal of the American College of Radiology : JACR
The multitude of artificial intelligence (AI)-based solutions, vendors, and platforms poses a challenging proposition to an already complex clinical radiology practice. Apart from assessing and ensuring acceptable local performance and workflow fit t...

Ontologies in the New Computational Age of Radiology: RadLex for Semantics and Interoperability in Imaging Workflows.

Radiographics : a review publication of the Radiological Society of North America, Inc
From basic research to the bedside, precise terminology is key to advancing medicine and ensuring optimal and appropriate patient care. However, the wide spectrum of diseases and their manifestations superimposed on medical team-specific and discipli...

The top 100 most cited articles on artificial intelligence in radiology: a bibliometric analysis.

Clinical radiology
AIM: To identify the most influential publications relating to artificial intelligence (AI) in radiology in order to identify current trends in the literature and to highlight areas requiring further research.

DECIDE-AI: a new reporting guideline and its relevance to artificial intelligence studies in radiology.

Clinical radiology
DECIDE-AI is a new, stage-specific reporting guideline for the early and live clinical evaluation of decision-support systems based on artificial intelligence (AI). It answers a need for more attention to the human factors influencing clinical AI per...

The time is now: making the case for a UK registry of deployment of radiology artificial intelligence applications.

Clinical radiology
Artificial intelligence (AI)-based healthcare applications (apps) are rapidly evolving, and radiology is a target specialty for their implementation. In this paper, we put the case for a national deployment registry to track the spread of AI apps int...

Natural language processing in narrative breast radiology reporting in University Malaya Medical Centre.

Health informatics journal
Radiology reporting is narrative, and its content depends on the clinician's ability to interpret the images accurately. A tertiary hospital, such as anonymous institute, focuses on writing reports narratively as part of training for medical personne...

Artificial intelligence in veterinary care will be a major driving force behind ai advancements in healthcare.

Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association