AIMC Topic: Radiologists
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Accuracy of radiologists and radiology residents in detection of paediatric appendicular fractures with and without artificial intelligence.
BMJ health & care informatics
Dec 5, 2024
OBJECTIVES: We aim to evaluate the accuracy of radiologists and radiology residents in the detection of paediatric appendicular fractures with and without the help of a commercially available fracture detection artificial intelligence (AI) solution i...
Effect of Artificial Intelligence as a Second Reader on the Lung Nodule Detection and Localization Accuracy of Radiologists and Non-radiology Physicians in Chest Radiographs: A Multicenter Reader Study.
Academic radiology
Nov 25, 2024
RATIONALE AND OBJECTIVES: Missed nodules in chest radiographs (CXRs) are common occurrences. We assessed the effect of artificial intelligence (AI) as a second reader on the accuracy of radiologists and non-radiology physicians in lung nodule detecti...
Aged
Radiographic Image Interpretation, Computer-Assisted
Tomography, X-Ray Computed
Humans
Observer Variation
Sensitivity and Specificity
Middle Aged
Radiography, Thoracic
Artificial Intelligence
Female
Male
Lung Neoplasms
Retrospective Studies
Reproducibility of Results
Solitary Pulmonary Nodule
Radiologists
The Promise of AI for Image-Driven Medicine: Qualitative Interview Study of Radiologists' and Pathologists' Perspectives.
JMIR human factors
Nov 21, 2024
BACKGROUND: Image-driven specialisms such as radiology and pathology are at the forefront of medical artificial intelligence (AI) innovation. Many believe that AI will lead to significant shifts in professional roles, so it is vital to investigate ho...
Burnout crisis in Chinese radiology: will artificial intelligence help?
European radiology
Nov 20, 2024
OBJECTIVES: To assess the correlation between the use of artificial intelligence (AI) software and burnout in the radiology departments of hospitals in China.
Artificial intelligence: a primer for pediatric radiologists.
Pediatric radiology
Nov 18, 2024
Artificial intelligence (AI) is increasingly recognized for its transformative potential in radiology; yet, its application in pediatric radiology is relatively limited when compared to the whole of radiology. This manuscript introduces pediatric rad...
Collaboration between clinicians and vision-language models in radiology report generation.
Nature medicine
Nov 7, 2024
Automated radiology report generation has the potential to improve patient care and reduce the workload of radiologists. However, the path toward real-world adoption has been stymied by the challenge of evaluating the clinical quality of artificial i...
Artificial Intelligence and Radiologist Burnout.
JAMA network open
Nov 4, 2024
IMPORTANCE: Understanding the association of artificial intelligence (AI) with physician burnout is crucial for fostering a collaborative interactive environment between physicians and AI.
Radiographer Education and Learning in Artificial Intelligence (REAL-AI): A survey of radiographers, radiologists, and students' knowledge of and attitude to education on AI.
Radiography (London, England : 1995)
Oct 30, 2024
INTRODUCTION: In Autumn 2023, amendments to the Health and Care Professions Councils (HCPC) Standards of Proficiency for Radiographers were introduced requiring clinicians to demonstrate awareness of the principles of AI and deep learning technology,...
Current Radiology workforce perspective on the integration of artificial intelligence in clinical practice: A systematic review.
Journal of medical imaging and radiation sciences
Oct 21, 2024
INTRODUCTION: Artificial Intelligence (AI) represents the application of computer systems to tasks traditionally performed by humans. The medical imaging profession has experienced a transformative shift through the integration of AI. While there hav...
Enhancing Radiologists' Performance in Detecting Cerebral Aneurysms Using a Deep Learning Model: A Multicenter Study.
Academic radiology
Oct 15, 2024
RATIONALE AND OBJECTIVES: This study aimed to develop a deep learning (DL)-based model for detecting and diagnosing cerebral aneurysms in clinical settings, with and without human assistance.
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