AIMC Topic: Radiology
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RADHawk-an AI-based knowledge recommender to support precision education, improve reporting productivity, and reduce cognitive load.
Pediatric radiology
Dec 7, 2024
BACKGROUND: Using artificial intelligence (AI) to augment knowledge is key to establishing precision education in modern radiology training. Our department has developed a novel AI-derived knowledge recommender, the first reported precision education...
Inclusive AI for radiology: Optimising ChatGPT-4 with advanced prompt engineering.
Clinical imaging
Dec 6, 2024
This letter responds to the article "Encouragement vs. liability: How prompt engineering influences ChatGPT-4's radiology exam performance," offering additional perspectives on optimising ChatGPT-4 for Radiology applications. While the study highligh...
ESR Essentials: how to get to valuable radiology AI: the role of early health technology assessment-practice recommendations by the European Society of Medical Imaging Informatics.
European radiology
Dec 5, 2024
AI tools in radiology are revolutionising the diagnosis, evaluation, and management of patients. However, there is a major gap between the large number of developed AI tools and those translated into daily clinical practice, which can be primarily at...
Accuracy of radiologists and radiology residents in detection of paediatric appendicular fractures with and without artificial intelligence.
BMJ health & care informatics
Dec 5, 2024
OBJECTIVES: We aim to evaluate the accuracy of radiologists and radiology residents in the detection of paediatric appendicular fractures with and without the help of a commercially available fracture detection artificial intelligence (AI) solution i...
Large Language Models with Vision on Diagnostic Radiology Board Exam Style Questions.
Academic radiology
Dec 4, 2024
RATIONALE AND OBJECTIVES: The expansion of large language models to process images offers new avenues for application in radiology. This study aims to assess the multimodal capabilities of contemporary large language models, which allow analysis of i...
Multi-modal large language models in radiology: principles, applications, and potential.
Abdominal radiology (New York)
Dec 2, 2024
Large language models (LLMs) and multi-modal large language models (MLLMs) represent the cutting-edge in artificial intelligence. This review provides a comprehensive overview of their capabilities and potential impact on radiology. Unlike most exist...
Avoiding missed opportunities in AI for radiology.
International journal of computer assisted radiology and surgery
Nov 25, 2024
PURPOSE: In the last decade, the development of Deep Learning and its variants, based on the application of artificial neural networks, has reinvigorated Artificial Intelligence (AI). As a result, many new applications of AI in medicine, especially R...
Burnout crisis in Chinese radiology: will artificial intelligence help?
European radiology
Nov 20, 2024
OBJECTIVES: To assess the correlation between the use of artificial intelligence (AI) software and burnout in the radiology departments of hospitals in China.
Artificial intelligence: a primer for pediatric radiologists.
Pediatric radiology
Nov 18, 2024
Artificial intelligence (AI) is increasingly recognized for its transformative potential in radiology; yet, its application in pediatric radiology is relatively limited when compared to the whole of radiology. This manuscript introduces pediatric rad...
Manual data labeling, radiology, and artificial intelligence: It is a dirty job, but someone has to do it.
Magnetic resonance imaging
Nov 16, 2024
In this letter to the editor, authors highlight the key role of data labeling in training AI models for medical imaging, discussing the complexities, resource demands, costs, and the relevance of quality control in the labeling process including the ...
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