The applications of artificial intelligence (AI) in radiology are rapidly advancing with AI algorithms being used in a wide range of disease pathologies and clinical settings. Acute thoracic pathologies including rib fractures, pneumothoraces, and acute PE are associated with significant morbidity and mortality and their identification is crucial for prompt treatment. AI models which increase diagnostic accuracy, improve radiologist efficiency and reduce time to diagnosis of acute abnormalities in the thorax have the potential to significantly improve patient outcomes. The purpose of this review is to summarize the current applications of AI in acute thoracic imaging, highlighting their strengths, limitations, and future research opportunities.
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Objectives: This study evaluates a staged selective hybrid approach for acute type A aortic dissection. The approach involves a zone 2 aortic arch replacement with debranching of the brachiocephalic trunk and left common carotid artery to create a landing zone for thoracic endovascular aortic repair. This repair is performed either preemptively in the subacute phase to promote remodelling or electively in the chronic phase to manage aneurysm formation.
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Liverpool Centre for Cardiovascular Sciences, Liverpool Heart and Chest Hospital, Liverpool, UK.
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