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Artificial Intelligence May Help Radiologists Detect Fractures in Daily Practice In a recent paper published in Radiology, Guermazi et. al. used artificial intelligence (AI) algorithm for automatically detecting X-rays that are positive for fractures. They showed AI assistance helped reduce missed fractures by 29 per cent and increased readers’ sensitivity by 16 per cent, and by 30 per cent for exams with more than one fracture, while improving specificity by 5 per cent. They concluded that AI can be a powerful tool to help radiologists and other physicians to improve diagnostic performance and increase efficiency, while potentially improving patient experience at the time of hospital or clinic visit. Ali Guermazi, Professor of Radiology and Medicine, Boston University Nor-Eddine Regnard, Radiologist
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issed fractures on standard radiographs are one of the most common causes of medical errors in the emergency department and can lead to potentially serious complications, delays in diagnostic and therapeutic management, and the risk of legal claims by patients. In a study recently published in Radiology, Prof. Ali Guermazi et. al. Showed an improvement in clinicians' diagnostic performance in detecting fractures in standard radiography using artificial intelligence software, BoneView by Gleamer, compared to reading radiographs without assistance. This was a retrospective study including 480 radiographic examinations of adults over 21 years of age, with indications of trauma and fracture prevalence of 50 per cent. Radiographs included were of the limbs, pelvis, dorsal spine, lumbar spine and rib cages.
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