AIMC Topic: Radiology

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Decoding medical jargon: The use of AI language models (ChatGPT-4, BARD, microsoft copilot) in radiology reports.

Patient education and counseling
OBJECTIVE: Evaluate Artificial Intelligence (AI) language models (ChatGPT-4, BARD, Microsoft Copilot) in simplifying radiology reports, assessing readability, understandability, actionability, and urgency classification.

Artificial intelligence improves resident detection of pediatric and young adult upper extremity fractures.

Skeletal radiology
PURPOSE: We wished to evaluate if an open-source artificial intelligence (AI) algorithm ( https://www.childfx.com ) could improve performance of (1) subspecialized musculoskeletal radiologists, (2) radiology residents, and (3) pediatric residents in ...

Choosing the right artificial intelligence solutions for your radiology department: key factors to consider.

Diagnostic and interventional radiology (Ankara, Turkey)
The rapid evolution of artificial intelligence (AI), particularly in deep learning, has significantly impacted radiology, introducing an array of AI solutions for interpretative tasks. This paper provides radiology departments with a practical guide ...

Applications of deep learning in trauma radiology: A narrative review.

Biomedical journal
Diagnostic imaging is essential in modern trauma care for initial evaluation and identifying injuries requiring intervention. Deep learning (DL) has become mainstream in medical image analysis and has shown promising efficacy for classification, segm...

Artificial Intelligence in Radiology: What Is Its True Role at Present, and Where Is the Evidence?

Radiologic clinics of North America
The integration of artificial intelligence (AI) in radiology has brought about substantial advancements and transformative potential in diagnostic imaging practices. This study presents an overview of the current research on the application of AI in ...

The virtual reference radiologist: comprehensive AI assistance for clinical image reading and interpretation.

European radiology
OBJECTIVES: Large language models (LLMs) have shown potential in radiology, but their ability to aid radiologists in interpreting imaging studies remains unexplored. We investigated the effects of a state-of-the-art LLM (GPT-4) on the radiologists' d...

From Bench to Bedside With Large Language Models: Expert Panel Narrative Review.

AJR. American journal of roentgenology
Large language models (LLMs) hold immense potential to revolutionize radiology. However, their integration into practice requires careful consideration. Artificial intelligence (AI) chatbots and general-purpose LLMs have potential pitfalls related to...

AI in radiology: Legal responsibilities and the car paradox.

European journal of radiology
The integration of AI in radiology raises significant legal questions about responsibility for errors. Radiologists fear AI may introduce new legal challenges, despite its potential to enhance diagnostic accuracy. AI tools, even those approved by reg...