AI Medical Compendium Topic

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Radiology

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Explainability of radiomics through formal methods.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Artificial Intelligence has proven to be effective in radiomics. The main problem in using Artificial Intelligence is that researchers and practitioners are not able to know how the predictions are generated. This is current...

Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE).

European radiology
OBJECTIVE: There has been a large amount of research in the field of artificial intelligence (AI) as applied to clinical radiology. However, these studies vary in design and quality and systematic reviews of the entire field are lacking.This systemat...

The role of artificial intelligence in paediatric neuroradiology.

Pediatric radiology
Imaging plays a fundamental role in the managing childhood neurologic, neurosurgical and neuro-oncological disease. Employing multi-parametric MRI techniques, such as spectroscopy and diffusion- and perfusion-weighted imaging, to the radiophenotyping...

Physicians' preferences and willingness to pay for artificial intelligence-based assistance tools: a discrete choice experiment among german radiologists.

BMC health services research
BACKGROUND: Artificial Intelligence (AI)-based assistance tools have the potential to improve the quality of healthcare when adopted by providers. This work attempts to elicit preferences and willingness to pay for these tools among German radiologis...

What Influences the Way Radiologists Express Themselves in Their Reports? A Quantitative Assessment Using Natural Language Processing.

Journal of digital imaging
Although using standardized reports is encouraged, most emergency radiological reports in France remain in free-text format that can be mined with natural language processing for epidemiological purposes, activity monitoring or data collection. These...

Deep learning models in medical image analysis.

Journal of oral biosciences
BACKGROUND: Deep learning is a state-of-the-art technology that has rapidly become the method of choice for medical image analysis. Its fast and robust object detection, segmentation, tracking, and classification of pathophysiological anatomical stru...

[Artificial intelligence (AI) in radiology? : Do we need as many radiologists in the future?].

Der Urologe. Ausg. A
We are in the middle of a digital revolution in medicine. This raises the question of whether subjects such as radiology, which is superficially concerned with the interpretation of images, will be particularly changed by this revolution. In particul...

Workflow Integration of Research AI Tools into a Hospital Radiology Rapid Prototyping Environment.

Journal of digital imaging
The field of artificial intelligence (AI) in medical imaging is undergoing explosive growth, and Radiology is a prime target for innovation. The American College of Radiology Data Science Institute has identified more than 240 specific use cases wher...

Autonomous artificial intelligence in pediatric radiology: the use and perception of BoneXpert for bone age assessment.

Pediatric radiology
BACKGROUND: The autonomous artificial intelligence (AI) system for bone age rating (BoneXpert) was designed to be used in clinical radiology practice as an AI-replace tool, replacing the radiologist completely.

Non-radiologist perception of the use of artificial intelligence (AI) in diagnostic medical imaging reports.

Journal of medical imaging and radiation oncology
INTRODUCTION: Incorporating artificial intelligence (AI) in diagnostic medical imaging reports has the potential to improve efficiency. Although perception of radiologists, radiographers, medical students and patients on AI use in image reporting has...