الفهرس 
Radiation safety measuresOnly 14 pages are availabe for public view
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Abstract
chest radiography is the most common imaging modality in the world. Timely radiologist reporting of every image is not always possible due to heavy workload in many large healthcare centers or the lack of experienced radiologists in less developed areas.
However, using the AI as an aid has proven to improve the overall performance of radiology resident allowing them to reach expert like levels of diagnostic performance in the CXR interpretation.
In this study we found that the resident accuracy and sensitivity increase across a large number of clinical chest x-ray findings when assisted by the deep-learning model. Effective implementation of the model has the potential to improve clinical practice. Research is underway to assess the generalizability of results to various clinical environments and health systems.
We also raised the possibility of the potential use of AI systems in future radiology workflows for preliminary interpretations that target the most prevalent findings, leaving the final reads to be done by a more experienced radiologist in a suitable practice atmosphere to catch any potential misses from the less-prevalent fine-grained findings.