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Radiology

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Update on ethical aspects in clinical research: Addressing concerns in the development of new AI tools in radiology.

Radiologia
The analysis of ethical aspects in clinical research has always been a challenge and has required constant updates. In short, research ethics is the set of specific principles, rules, and norms of behavior that a research community has decided are ap...

[Artificial intelligence in radiology : Literature overview and reading recommendations].

Radiologie (Heidelberg, Germany)
BACKGROUND: Due to the ongoing rapid advancement of artificial intelligence (AI), including large language models (LLMs), radiologists will soon face the challenge of the responsible clinical integration of these models.

Large language models in methodological quality evaluation of radiomics research based on METRICS: ChatGPT vs NotebookLM vs radiologist.

European journal of radiology
OBJECTIVES: This study aimed to evaluate the effectiveness of large language models (LLM) in assessing the methodological quality of radiomics research, using METhodological RadiomICs Score (METRICS) tool.

Performance Evaluation and Implications of Large Language Models in Radiology Board Exams: Prospective Comparative Analysis.

JMIR medical education
BACKGROUND: Artificial intelligence advancements have enabled large language models to significantly impact radiology education and diagnostic accuracy.

Artificial Intelligence in Radiology: A Leadership Survey.

Journal of the American College of Radiology : JACR
PURPOSE: Surveys to assess views about artificial intelligence (AI) of various diagnostic radiology constituencies have revealed interesting combinations of enthusiasm, caution, and implementation priorities. We surveyed academic radiology leaders ab...

The need for balancing 'black box' systems and explainable artificial intelligence: A necessary implementation in radiology.

European journal of radiology
Radiology is one of the medical specialties most significantly impacted by Artificial Intelligence (AI). AI systems, particularly those employing machine and deep learning, excel in processing large datasets and comparing images from similar contexts...

The radiologist as an independent "third party" to the patient and clinicians in the era of generative AI.

La Radiologia medica
Radiologists are crucial in the diagnostic workflow. They must maintain an independent perspective, being a "third party" to the patients and referral clinicians. This is important when documenting the absence of relevant abnormalities or providing i...

Foundation Models in Radiology: What, How, Why, and Why Not.

Radiology
Recent advances in artificial intelligence have witnessed the emergence of large-scale deep learning models capable of interpreting and generating both textual and imaging data. Such models, typically referred to as foundation models (FMs), are train...

LHR-RFL: Linear Hybrid-Reward-Based Reinforced Focal Learning for Automatic Radiology Report Generation.

IEEE transactions on medical imaging
Radiology report generation that aims to accurately describe medical findings for given images, is pivotal in contemporary computer-aided diagnosis. Recently, despite considerable progress, current radiology report generation models still struggled t...

Increasing Accessibility: Effectiveness of a Remote Artificial Intelligence Education Curriculum for International Medical Graduates.

The clinical teacher
BACKGROUND: Applications of artificial intelligence (AI) in medicine are expanding every year. AI education is crucial to its appropriate use in healthcare; however, most US medical schools lack a dedicated AI curriculum. These resources are sparse f...