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 in the hopes of showing potential clinical benefits in a general hospital setting.
Methods: This was a retrospective study involving three associate consultants (AC) and three senior residents (SR) in radiology, who acted as readers. One reader from each human group interpreted the radiographs with the aid of AI.
BACKGROUND Facet joint septic arthritis (SAFJ) is a rare clinical entity that is extremely challenging to diagnose, often presenting unilaterally and with nonspecific clinical symptoms. However, SAFJ has significant morbidity and mortality, especially with delayed diagnosis. It becomes all the more important for the clinician to recognize that SAFJ can present bilaterally and be associated with direct inoculation, such as in acupuncture.
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