AIMC Topic: Radiology

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Large Language Model Use in Radiology Residency Applications: Unwelcomed but Inevitable.

Journal of the American College of Radiology : JACR
OBJECTIVE: This study explores radiology program directors' perspectives on the impact of large language model (LLM) use among residency applicants to craft personal statements.

Assessing the Emergence and Evolution of Artificial Intelligence and Machine Learning Research in Neuroradiology.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Interest in artificial intelligence (AI) and machine learning (ML) has been growing in neuroradiology, but there is limited knowledge on how this interest has manifested into research and specifically, its qualities and charac...

Artificial Intelligence in the Training of Radiology Residents: a Multicenter Randomized Controlled Trial.

Journal of cancer education : the official journal of the American Association for Cancer Education
The aim of the present study was to compare the effectiveness of AI-assisted training and conventional human training in clinical practice. This was a multicenter, randomized, controlled clinical trial conducted in five national-level residency train...

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.