AIMC Topic: Radiology

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Integration of artificial intelligence in radiology education: a requirements survey and recommendations from faculty radiologists, residents, and medical students.

BMC medical education Mar 13, 2025
BACKGROUND: To investigate the perspectives and expectations of faculty radiologists, residents, and medical students regarding the integration of artificial intelligence (AI) in radiology education, a survey was conducted to collect their opinions a...
Radiology Radiologists Faculty, Medical Internship and Residency Artificial Intelligence Surveys and Questionnaires Female Attitude of Health Personnel Adult Students, Medical Humans Male
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Artificial Intelligence for Teaching Case Curation: Evaluating Model Performance on Imaging Report Discrepancies.

Academic radiology Mar 9, 2025
RATIONALE AND OBJECTIVES: Assess the feasibility of using a large language model (LLM) to identify valuable radiology teaching cases through report discrepancy detection.
Humans Artificial Intelligence Sensitivity and Specificity Radiology Feasibility Studies Retrospective Studies Tomography, X-Ray Computed Internship and Residency
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The Road Map for ACR Practice Accreditation for Radiology Artificial Intelligence.

Journal of the American College of Radiology : JACR Mar 8, 2025
As the use of artificial intelligence (AI) continues to grow in radiology, it has become clear that its real-world performance often differs from that demonstrated in premarket testing, underscoring the need for robust quality management (QM) program...
Quality Assurance, Health Care Societies, Medical United States Accreditation Radiology Humans Artificial Intelligence
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Exploring Curriculum Considerations to Prepare Future Radiographers for an AI-Assisted Health Care Environment: Protocol for Scoping Review.

JMIR research protocols Mar 6, 2025
BACKGROUND: The use of artificial intelligence (AI) technologies in radiography practice is increasing. As this advanced technology becomes more embedded in radiography systems and clinical practice, the role of radiographers will evolve. In the cont...
Humans Artificial Intelligence Curriculum Scoping Review as Topic Research Design Radiology
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Artificial Intelligence-Generated Editorials in Radiology: Can Expert Editors Detect Them?

AJNR. American journal of neuroradiology Mar 4, 2025
BACKGROUND AND PURPOSE: Artificial intelligence is capable of generating complex texts that may be indistinguishable from those written by humans. We aimed to evaluate the ability of GPT-4 to write radiology editorials and to compare these with human...
Publishing Periodicals as Topic Humans Artificial Intelligence Editorial Policies Radiology
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Artificial Intelligence user interface preferences in radiology: A scoping review.

Journal of medical imaging and radiation sciences Feb 27, 2025
INTRODUCTION/BACKGROUND: Modern forms of Artificial intelligence (AI) have developed in radiology over the past few years. With the current workforce shortages, in both radiology and radiography professions, AI continues to prove its place in support...
Artificial Intelligence User-Computer Interface Radiology Humans
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The need for balancing 'black box' systems and explainable artificial intelligence: A necessary implementation in radiology.

European journal of radiology Feb 26, 2025
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...
Artificial Intelligence Radiology Humans Informed Consent
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The radiologist as an independent "third party" to the patient and clinicians in the era of generative AI.

La Radiologia medica Feb 26, 2025
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...
Radiology Radiologists Humans Artificial Intelligence Physician-Patient Relations Communication
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Enhancing diagnostic accuracy of thyroid nodules: integrating self-learning and artificial intelligence in clinical training.

Endocrine Feb 20, 2025
PURPOSE: This study explores a self-learning method as an auxiliary approach in residency training for distinguishing between benign and malignant thyroid nodules.
Radiology Internal Medicine Thyroid Neoplasms Thyroid Nodule Adult Internship and Residency Male Diagnosis, Computer-Assisted Humans Clinical Competence Artificial Intelligence Female
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[Artificial intelligence in radiology : Literature overview and reading recommendations].

Radiologie (Heidelberg, Germany) Feb 4, 2025
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.
Radiology Humans Artificial Intelligence
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