AIMC Topic: Radiology

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Conceptual review of outcome metrics and measures used in clinical evaluation of artificial intelligence in radiology.

La Radiologia medica
Artificial intelligence (AI) has numerous applications in radiology. Clinical research studies to evaluate the AI models are also diverse. Consequently, diverse outcome metrics and measures are employed in the clinical evaluation of AI, presenting a ...

Facilitating the use of routine data to evaluate artificial intelligence solutions: lessons from the NIHR/RCR data curation workshop.

Clinical radiology
Radiology currently stands at the forefront of artificial intelligence (AI) development and deployment over many other medical subspecialities within the scope of both research and clinical practice. Given this current leadership position, it is impe...

Interactive dual-stream contrastive learning for radiology report generation.

Journal of biomedical informatics
Radiology report generation automates diagnostic narrative synthesis from medical imaging data. Current report generation methods primarily employ knowledge graphs for image enhancement, neglecting the interpretability and guiding function of the kno...

Potential strength and weakness of artificial intelligence integration in emergency radiology: a review of diagnostic utilizations and applications in patient care optimization.

Emergency radiology
Artificial intelligence (AI) and its recent increasing healthcare integration has created both new opportunities and challenges in the practice of radiology and medical imaging. Recent advancements in AI technology have allowed for more workplace eff...

[Applications of artificial intelligence in radiology].

Radiologie (Heidelberg, Germany)
BACKGROUND: Artificial intelligence (AI) is increasingly finding its way into routine radiological work.

2023 Industry Perceptions Survey on AI Adoption and Return on Investment.

Journal of imaging informatics in medicine
This SIIM-sponsored 2023 report highlights an industry view on artificial intelligence adoption barriers and success related to diagnostic imaging, life sciences, and contrasts. In general, our 2023 survey indicates that there has been progress in ad...

From Revisions to Insights: Converting Radiology Report Revisions into Actionable Educational Feedback Using Generative AI Models.

Journal of imaging informatics in medicine
Expert feedback on trainees' preliminary reports is crucial for radiologic training, but real-time feedback can be challenging due to non-contemporaneous, remote reading and increasing imaging volumes. Trainee report revisions contain valuable educat...

Artificial intelligence in musculoskeletal applications: a primer for radiologists.

Diagnostic and interventional radiology (Ankara, Turkey)
As an umbrella term, artificial intelligence (AI) covers machine learning and deep learning. This review aimed to elaborate on these terms to act as a primer for radiologists to learn more about the algorithms commonly used in musculoskeletal radiolo...