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Radiology

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Assessing AI-Powered Patient Education: A Case Study in Radiology.

Academic radiology
RATIONALE AND OBJECTIVES: With recent advancements in the power and accessibility of artificial intelligence (AI) Large Language Models (LLMs) patients might increasingly turn to these platforms to answer questions regarding radiologic examinations a...

AI pitfalls and what not to do: mitigating bias in AI.

The British journal of radiology
Various forms of artificial intelligence (AI) applications are being deployed and used in many healthcare systems. As the use of these applications increases, we are learning the failures of these models and how they can perpetuate bias. With these n...

AI in medical imaging grand challenges: translation from competition to research benefit and patient care.

The British journal of radiology
Artificial intelligence (AI), in one form or another, has been a part of medical imaging for decades. The recent evolution of AI into approaches such as deep learning has dramatically accelerated the application of AI across a wide range of radiologi...

The unintended consequences of artificial intelligence in paediatric radiology.

Pediatric radiology
Over the past decade, there has been a dramatic rise in the interest relating to the application of artificial intelligence (AI) in radiology. Originally only 'narrow' AI tasks were possible; however, with increasing availability of data, teamed with...

Generative AI in Medical Imaging: Applications, Challenges, and Ethics.

Journal of medical systems
Medical imaging is playing an important role in diagnosis and treatment of diseases. Generative artificial intelligence (AI) have shown great potential in enhancing medical imaging tasks such as data augmentation, image synthesis, image-to-image tran...

Overcoming the Challenges in the Development and Implementation of Artificial Intelligence in Radiology: A Comprehensive Review of Solutions Beyond Supervised Learning.

Korean journal of radiology
Artificial intelligence (AI) in radiology is a rapidly developing field with several prospective clinical studies demonstrating its benefits in clinical practice. In 2022, the Korean Society of Radiology held a forum to discuss the challenges and dra...

[Large language models such as ChatGPT and GPT-4 for patient-centered care in radiology].

Radiologie (Heidelberg, Germany)
BACKGROUND: With the introduction of ChatGPT in late November 2022, large language models based on artificial intelligence have gained worldwide recognition. These language models are trained on vast amounts of data, enabling them to process complex ...

Closing the loop for AI-ready radiology.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
BACKGROUND: In recent years, AI has made significant advancements in medical diagnosis and prognosis. However, the incorporation of AI into clinical practice is still challenging and under-appreciated. We aim to demonstrate a possible vertical integr...